Test kits

ABSTRACT

This invention relates to prognostic signatures, and compositions and methods for determining the prognosis of cancer in a patient, particularly for colorectal cancer. Specifically, this invention relates to the use of genetic markers for the prediction of the prognosis of cancer, such as colorectal cancer, based on signatures of genetic markers. In various aspects, the invention relates to a method of predicting the likelihood of long-term survival of a cancer patient, a method of determining a treatment regime for a cancer patient, a method of preparing a treatment modality for a cancer patient, among other methods as well as kits and devices for carrying out these methods.

RELATED APPLICATIONS

This application is a Divisional application filed under 35 U.S.C. §120and 37 C.F.R. 1.53(b), which claims priority to U.S. patent applicationSer. No. 13/214,782, which is a Continuation under 35 U.S.C. §1.111(a)of PCT/NZ2006/000343, International Filing Date 22 Dec. 2006, whichclaims the benefit of New Zealand Provisional Patent Application No.544432 filed Dec. 23, 2005, each of which is incorporated by referenceherein in its entirety.

FIELD OF THE INVENTION

This invention relates to test kits, methods and compositions fordetermining the prognosis of cancer, particularly colorectal cancer, ina patient. Specifically, this invention relates to the use of geneticmarkers for determining the prognosis of cancer, such as colorectalcancer, based on prognostic signatures.

BACKGROUND OF THE INVENTION

Colorectal cancer (CRC) is one of the most common cancers in thedeveloped world, and its incidence is continuing to increase. Althoughthe progression of colorectal cancer from benign polyp to adenoma tocarcinoma is well studied (1), the molecular events influencing thetransition and establishment of metastasis are less well understood. Theprognosis and treatment of CRC currently depends on theclinico-pathological stage of disease at the time of diagnosis, andprimary surgical treatment. Unfortunately disease stage alone does notallow accurate prediction of outcome for individual patients. If patientoutcomes could be predicted more accurately treatments could be tailoredto avoid under-treating patients destined to relapse, or over-treatingpatients who would be helped by surgery alone.

Many attempts have been made to identify markers that predict clinicaloutcome in CRC. Until recently most studies focused on single proteinsor gene mutations with limited success in terms of prognosticinformation (2). Microarray technology enables the identification ofsets of genes, called classifiers or signatures that correlate withcancer outcome. This approach has been applied to a variety of cancers,including CRC (3-5), but methodological problems and a lack ofindependent validation has cast doubt over the findings (6,7).Furthermore, doubts about the ability of classifiers/signatures topredict outcome have arisen due to poor concordance of identified bydifferent researchers using different array platforms and methodologies(8).

There is a need for further tools to predict the prognosis of colorectalcancer. This invention provides further methods, compositions, kits, anddevices based on prognostic cancer markers, specifically colorectalcancer prognostic markers, to aid in the prognosis and treatment ofcancer.

SUMMARY OF THE INVENTION

In certain embodiments there is provided a set of markers genesidentified to be differentially expressed in recurrent and non-recurrentcolorectal tumours. This set of genes and test kits can be used togenerate prognostics signatures, comprising two or more markers, capableof predicting the progression of colorectal tumour in a patient.

The individual markers can differentially expressed depending on whetherthe tumour is recurrent or not. The accuracy of prediction can beenhanced by combining the markers together into a prognostic signaturefor, providing for much more effective individual tests than single-geneassays. Also provided for is the application of techniques, such asstatistics, machine learning, artificial intelligence, and data miningto the prognostics signatures to generate prediction models. In anotherembodiment, expression levels of the markers of a particular prognosticsignature in the tumour of a patient can then be applied to theprediction model to determine the prognosis.

In certain embodiments, the expression level of the markers can beestablished using microarray methods, quantitative polymerase chainreaction (qPCR), or immunoassays.

BRIEF DESCRIPTION OF THE FIGURES

This invention is described with reference to specific embodimentsthereof and with reference to the figures, in which:

FIG. 1 depicts a flow chart showing the methodology for producing theprognostic signatures from 149 New Zealand (NZ) and 55 German (DE)colorectal cancer (CRC) samples. New Zealand RNA samples were hybridizedto oligonucleotide spotted arrays, with a 22-gene signature produced vialeave one out cross validation (LOOCV), and then independently validatedby LOOCV using the 55 sample DE data set. German RNA samples werehybridized to Affymetrix arrays, with a 19-gene signature produced viaLOOCV, and then independently validated by LOOCV using the NZ data set.

FIG. 2 depicts a Kaplan-Meier analysis of disease-free survival timewith patients predicted as high versus low risk of tumour recurrence:FIG. 2 a, using NZ 22-gene signature on 149 tumours from NZ patients;FIG. 2 b, using DE 19-gene signature on 55 tumours from DE patients;FIG. 2 c, NZ prognostic signature validated on 55 tumours from DEpatients; FIG. 2 d, DE prognostic signature validated on 149 tumoursfrom NZ patients. P-values were calculated using the log-rank test.

FIG. 3 depicts a Kaplan-Meier analysis of disease free survival timewith patients predicted as high versus low risk of tumour recurrence:FIG. 3 a, using the 22-gene NZ signature on NZ patients with Stage IIand Stage III disease; FIG. 3 b, using the 19-gene DE signature on NZpatients with Stage II and Stage III disease.

FIG. 4 shows the predictive value of signatures of varying lengths forprognosis of colorectal cancer. These signatures were derived from 10replicate runs of 11-fold cross validation. Each replicate 11-foldvalidation run is indicated by the various dashed lines; the mean acrossreplicates by the bold line. In each fold of the cross-validation, geneswere removed if the fold-change across classes was <1.1 (for theremaining samples not removed in that particular fold). The genes werethen ranked using a modified t-statistic, obtaining a different set ofgenes for each fold, and classifiers using the top n− genes (where n=2to 200) were constructed for each fold. The genes therefore may differfor each fold of each replicate 11-fold cross validation. FIG. 4 (A):Sensitivity (proportion of recurrent tumours correctly classified), withrespect to number of genes/signature. FIG. 4 (B): Specificity(proportion of non-recurrent tumours correctly classified), with respectto number of genes/signature. FIG. 4 (C): Classification rate(proportion of tumours correctly classified), with respect to number ofgenes/signature. The nomenclature applied by the statistician is asfollows: I refers to Stage I or Stage II colorectal cancer (with noprogression), and IV refers to eventual progression to Stage IVmetastases.

FIG. 5 shows the decreased predictive value of signatures for theprognosis of colorectal cancer, in a repeat of the experiment of FIG. 4,except with the two genes, FAS and ME2, removed from the data set. FIG.5 (A): Sensitivity (proportion of recurrent tumours correctlyclassified), with respect to number of genes/signature. FIG. 5 (B):Specificity (proportion of non-recurrent tumours correctly classified),with respect to number of genes/signature. FIG. 5 (C): Classificationrate (proportion of tumours correctly classified), with respect tonumber of genes/signature.

FIG. 6 shows a pairs chart of “top counts” (number of times each geneappeared in the “top-n” gene lists, i.e., top 10, top 20, top 100, andtop 325 as described in Example 17) using three different normalizationmethods produced using the R statistical computing package(10,39), inaccordance with Example 17, below. The “pairs” chart is described in byBecker et al, in their treatise on the S Language (upon which R isbased; see reference 39). To compare methods, use row and column asdefined on the diagonal to obtain the scatter plot between those twomethods, analogous to reading distances off a distance chart on a map

FIG. 7 shows the pairs chart (39) of top counts (number of times eachgene appeared in the “top-n” gene lists, i.e., top 10, top 20, top 100,and top 325 as described in Example 17) using three different filteringstatistics: FIG. 7( a) two-sample Wilcoxon test (41), FIG. 7( b) t-test(modified using an ad-hoc correction factor in the denominator toabrogate the effect of low-variance genes falsely appearing assignificant) and FIG. 7( c) empirical Bayes as provided by the“limma”(10,40,42) package of Bioconductor (12,40).

DETAILED DESCRIPTION Definitions

Before describing embodiments of the invention in detail, it will beuseful to provide some definitions of terms used herein.

The term “marker” refers to a molecule that is associated quantitativelyor qualitatively with the presence of a biological phenomenon. Examplesof “markers” include a polynucleotide, such as a gene or gene fragment,RNA or RNA fragment; or a gene product, including a polypeptide such asa peptide, oligopeptide, protein, or protein fragment; or any relatedmetabolites, by products, or any other identifying molecules, such asantibodies or antibody fragments, whether related directly or indirectlyto a mechanism underlying the phenomenon. The markers of the inventioninclude the nucleotide sequences (e.g., GenBank sequences) as disclosedherein, in particular, the full-length sequences, any coding sequences,any fragments, or any complements thereof, and any measurable markerthereof as defined above.

The terms “CCPM” or “colorectal cancer prognostic marker” or “CCPMfamily member” refer to a marker with altered expression that isassociated with a particular prognosis, e.g., a higher or lowerlikelihood of recurrence of cancer, as described herein, but can excludemolecules that are known in the prior art to be associated withprognosis of colorectal cancer. It is to be understood that the termCCPM does not require that the marker be specific only for colorectaltumours. Rather, expression of CCPM can be altered in other types oftumours, including malignant tumours.

The terms “prognostic signature,” “signature,” and the like refer to aset of two or more markers, for example CCPMs, that when analysedtogether as a set allow for the determination of or prediction of anevent, for example the prognostic outcome of colorectal cancer. The useof a signature comprising two or more markers reduces the effect ofindividual variation and allows for a more robust prediction.Non-limiting examples of CCPMs are set forth in Tables 1, 2, 5, and 9,while non-limiting examples of prognostic signatures are set forth inTables 3, 4, 8A, 8B, and 9, herein. In the context of the presentinvention, reference to “at least one,” “at least two,” “at least five,”etc., of the markers listed in any particular set (e.g., any signature)means any one or any and all combinations of the markers listed.

The term “prediction method” is defined to cover the broader genus ofmethods from the fields of statistics, machine learning, artificialintelligence, and data mining, which can be used to specify a predictionmodel. These are discussed further in the Detailed Description section.

The term “prediction model” refers to the specific mathematical modelobtained by applying a prediction method to a collection of data. In theexamples detailed herein, such data sets consist of measurements of geneactivity in tissue samples taken from recurrent and non-recurrentcolorectal cancer patients, for which the class (recurrent ornon-recurrent) of each sample is known. Such models can be used to (1)classify a sample of unknown recurrence status as being one of recurrentor non-recurrent, or (2) make a probabilistic prediction (i.e., produceeither a proportion or percentage to be interpreted as a probability)which represents the likelihood that the unknown sample is recurrent,based on the measurement of mRNA expression levels or expressionproducts, of a specified collection of genes, in the unknown sample. Theexact details of how these gene-specific measurements are combined toproduce classifications and probabilistic predictions are dependent onthe specific mechanisms of the prediction method used to construct themodel.

“Sensitivity”, “specificity” (or “selectivity”), and “classificationrate”, when applied to the describing the effectiveness of predictionmodels mean the following:

“Sensitivity” means the proportion of truly positive samples that arealso predicted (by the model) to be positive. In a test for CRCrecurrence, that would be the proportion of recurrent tumours predictedby the model to be recurrent. “Specificity” or “selectivity” means theproportion of truly negative samples that are also predicted (by themodel) to be negative. In a test for CRC recurrence, this equates to theproportion of non-recurrent samples that are predicted to bynon-recurrent by the model. “Classification Rate” is the proportion ofall samples that are correctly classified by the prediction model (bethat as positive or negative).

As used herein “antibodies” and like terms refer to immunoglobulinmolecules and immunologically active portions of immunoglobulin (Ig)molecules, i.e., molecules that contain an antigen binding site thatspecifically binds (immunoreacts with) an antigen.

These include, but are not limited to, polyclonal, monoclonal, chimeric,single chain, Fc, Fab, Fab′, and Fab₂ fragments, and a Fab expressionlibrary. Antibody molecules relate to any of the classes IgG, IgM, IgA,IgE, and IgD, which differ from one another by the nature of heavy chainpresent in the molecule. These include subclasses as well, such as IgG1,IgG2, and others. The light chain may be a kappa chain or a lambdachain. Reference herein to antibodies includes a reference to allclasses, subclasses, and types. Also included are chimeric antibodies,for example, monoclonal antibodies or fragments thereof that arespecific to more than one source, e.g., a mouse or human sequence.Further included are camelid antibodies, shark antibodies or nanobodies.

The terms “cancer” and “cancerous” refer to or describe thephysiological condition in mammals that is typically characterized byabnormal or unregulated cell growth. Cancer and cancer pathology can beassociated, for example, with metastasis, interference with the normalfunctioning of neighbouring cells, release of cytokines or othersecretory products at abnormal levels, suppression or aggravation ofinflammatory or immunological response, neoplasia, premalignancy,malignancy, invasion of surrounding or distant tissues or organs, suchas lymph nodes, etc. Specifically included are colorectal cancers, suchas, bowel (e.g., large bowel), anal, and rectal cancers.

The term “colorectal cancer” includes cancer of the colon, rectum,and/or anus, and especially, adenocarcinomas, and may also includecarcinomas (e.g., squamous cloacogenic carcinomas), melanomas,lymphomas, and sarcomas. Epidermoid (nonkeratinizing squamous cell orbasaloid) carcinomas are also included. The cancer may be associatedwith particular types of polyps or other lesions, for example, tubularadenomas, tubulovillous adenomas (e.g., villoglandular polyps), villous(e.g., papillary) adenomas (with or without adenocarcinoma),hyperplastic polyps, hamartomas, juvenile polyps, polypoid carcinomas,pseudopolyps, lipomas, or leiomyomas. The cancer may be associated withfamilial polyposis and related conditions such as Gardner's syndrome orPeutz-Jeghers syndrome. The cancer may be associated, for example, withchronic fistulas, irradiated anal skin, leukoplakia, lymphogranulomavenereum, Bowen's disease (intraepithelial carcinoma), condylomaacuminatum, or human papillomavirus. In other aspects, the cancer may beassociated with basal cell carcinoma, extramammary Paget's disease,cloacogenic carcinoma, or malignant melanoma.

The terms “differentially expressed,” “differential expression,” andlike phrases, refer to a gene marker whose expression is activated to ahigher or lower level in a subject (e.g., test sample) having acondition, specifically cancer, such as colorectal cancer, relative toits expression in a control subject (e.g., reference sample). The termsalso include markers whose expression is activated to a higher or lowerlevel at different stages of the same condition; in recurrent ornon-recurrent disease; or in cells with higher or lower levels ofproliferation. A differentially expressed marker may be either activatedor inhibited at the polynucleotide level or polypeptide level, or may besubject to alternative splicing to result in a different polypeptideproduct. Such differences may be evidenced by a change in mRNA levels,surface expression, secretion or other partitioning of a polypeptide,for example.

Differential expression may include a comparison of expression betweentwo or more markers (e.g., genes or their gene products); or acomparison of the ratios of the expression between two or more markers(e.g., genes or their gene products); or a comparison of two differentlyprocessed products (e.g., transcripts or polypeptides) of the samemarker, which differ between normal subjects and diseased subjects; orbetween various stages of the same disease; or between recurring andnon-recurring disease; or between cells with higher and lower levels ofproliferation; or between normal tissue and diseased tissue,specifically cancer, or colorectal cancer. Differential expressionincludes both quantitative, as well as qualitative, differences in thetemporal or cellular expression pattern in a gene or its expressionproducts among, for example, normal and diseased cells, or among cellswhich have undergone different disease events or disease stages, orcells with different levels of proliferation.

The term “expression” includes production of polynucleotides andpolypeptides, in particular, the production of RNA (e.g., mRNA) from agene or portion of a gene, and includes the production of a polypeptideencoded by an RNA or gene or portion of a gene, and the appearance of adetectable material associated with expression. For example, theformation of a complex, for example, from a polypeptide-polypeptideinteraction, polypeptide-nucleotide interaction, or the like, isincluded within the scope of the term “expression”. Another example isthe binding of a binding ligand, such as a hybridization probe orantibody, to a gene or other polynucleotide or oligonucleotide, apolypeptide or a protein fragment, and the visualization of the bindingligand. Thus, the intensity of a spot on a microarray, on ahybridization blot such as a Northern blot, or on an immunoblot such asa Western blot, or on a bead array, or by PCR analysis, is includedwithin the term “expression” of the underlying biological molecule.

The terms “expression threshold,” and “defined expression threshold” areused interchangeably and refer to the level of a marker in questionoutside which the polynucleotide or polypeptide serves as a predictivemarker for patient survival without cancer recurrence. The thresholdwill be dependent on the predictive model established are derivedexperimentally from clinical studies such as those described in theExamples below. Depending on the prediction model used, the expressionthreshold may be set to achieve maximum sensitivity, or for maximumspecificity, or for minimum error (maximum classification rate). Forexample a higher threshold may be set to achieve minimum errors, butthis may result in a lower sensitivity. Therefore, for any givenpredictive model, clinical studies will be used to set an expressionthreshold that generally achieves the highest sensitivity while having aminimal error rate. The determination of the expression threshold forany situation is well within the knowledge of those skilled in the art.

The term “long-term survival” is used herein to refer to survival for atleast 5 years, more preferably for at least 8 years, most preferably forat least 10 years following surgery or other treatment.

The term “microarray” refers to an ordered or unordered arrangement ofcapture agents, preferably polynucleotides (e.g., probes) orpolypeptides on a substrate. See, e.g., Microarray Analysis, M. Schena,John Wiley & Sons, 2002; Microarray Biochip Technology, M. Schena, ed.,Eaton Publishing, 2000; Guide to Analysis of DNA Microarray Data, S.Knudsen, John Wiley & Sons, 2004; and Protein Microarray Technology, D.Kambhampati, ed., John Wiley & Sons, 2004.

The term “oligonucleotide” refers to a polynucleotide, typically a probeor primer, including, without limitation, single-strandeddeoxyribonucleotides, single- or double-stranded ribonucleotides, RNA:DNA hybrids, and double-stranded DNAs. Oligonucleotides, such assingle-stranded DNA probe oligonucleotides, are often synthesized bychemical methods, for example using automated oligonucleotidesynthesizers that are commercially available, or by a variety of othermethods, including in vitro expression systems, recombinant techniques,and expression in cells and organisms.

The term “polynucleotide,” when used in the singular or plural,generally refers to any polyribonucleotide or polydeoxribonucleotide,which may be unmodified RNA or DNA or modified RNA or DNA. Thisincludes, without limitation, single- and double-stranded DNA, DNAincluding single- and double-stranded regions, single- anddouble-stranded RNA, and RNA including single- and double-strandedregions, hybrid molecules comprising DNA and RNA that may besingle-stranded or, more typically, double-stranded or include single-and double-stranded regions. Also included are triple-stranded regionscomprising RNA or DNA or both RNA and DNA. Specifically included aremRNAs, cDNAs, and genomic DNAs, and any fragments thereof. The termincludes DNAs and RNAs that contain one or more modified bases, such astritiated bases, or unusual bases, such as inosine. The polynucleotidesof the invention can encompass coding or non-coding sequences, or senseor antisense sequences. It will be understood that each reference to a“polynucleotide” or like term, herein, will include the full-lengthsequences as well as any fragments, derivatives, or variants thereof.

“Polypeptide,” as used herein, refers to an oligopeptide, peptide, orprotein sequence, or fragment thereof, and to naturally occurring,recombinant, synthetic, or semi-synthetic molecules. Where “polypeptide”is recited herein to refer to an amino acid sequence of a naturallyoccurring protein molecule, “polypeptide” and like terms, are not meantto limit the amino acid sequence to the complete, native amino acidsequence for the full-length molecule. It will be understood that eachreference to a “polypeptide” or like term, herein, will include thefull-length sequence, as well as any fragments, derivatives, or variantsthereof.

The term “prognosis” refers to a prediction of medical outcome, forexample, a poor or good outcome (e.g., likelihood of long-termsurvival); a negative prognosis, or poor outcome, includes a predictionof relapse, disease progression (e.g., tumour growth or metastasis, ordrug resistance), or mortality; a positive prognosis, or good outcome,includes a prediction of disease remission, (e.g., disease-free status),amelioration (e.g., tumour regression), or stabilization.

The term “proliferation” refers to the processes leading to increasedcell size or cell number, and can include one or more of: tumour or cellgrowth, angiogenesis, innervation, and metastasis.

The term “qPCR” or “QPCR” refers to quantative polymerase chain reactionas described, for example, in PCR Technique: Quantitative PCR, J. W.Larrick, ed., Eaton Publishing, 1997, and A-Z of Quantitative PCR, S.Bustin, ed., IUL Press, 2004.

The term “tumour” refers to all neoplastic cell growth andproliferation, whether malignant or benign, and all pre-cancerous andcancerous cells and tissues.

“Stringency” of hybridization reactions is readily determinable by oneof ordinary skill in the art, and generally is an empirical calculationdependent upon probe length, washing temperature, and saltconcentration. In general, longer probes require higher temperatures forproper annealing, while shorter probes need lower temperatures.Hybridization generally depends on the ability of denatured DNA toreanneal when complementary strands are present in an environment belowtheir melting temperature. The higher the degree of desired homologybetween the probe and hybridisable sequence, the higher the relativetemperature which can be used. As a result, it follows that higherrelative temperatures would tend to make the reaction conditions morestringent, while lower temperatures less so. Additional details andexplanation of stringency of hybridization reactions, are found e.g., inAusubel et al., Current Protocols in Molecular Biology, WileyInterscience Publishers, (1995).

“Stringent conditions” or “high stringency conditions”, as definedherein, typically: (1) employ low ionic strength and high temperaturefor washing, for example 0.015 M sodium chloride/0.0015 M sodiumcitrate/0.1% sodium dodecyl sulfate at 50° C.; (2) employ a denaturingagent during hybridization, such as formamide, for example, 50% (v/v)formamide with 0.1% bovine serum albumin/0.1% Ficoll/0.1%polyvinylpyrrolidone/50 mM sodium phosphate buffer at pH 6.5 with 750 mMsodium chloride, 75 mM sodium citrate at 42° C.; or (3) employ 50%formamide, 5×SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodiumphosphate (pH 6.8), 0.1% sodium pyrophosphate, 5×, Denhardt's solution,sonicated salmon sperm DNA (50 μg/ml), 0.1% SDS, and 10% dextran sulfateat 42° C., with washes at 42° C. in 0.2×SSC (sodium chloride/sodiumcitrate) and 50% formamide at 55° C., followed by a high-stringency washcomprising 0.1×SSC containing EDTA at 55° C.

“Moderately stringent conditions” may be identified as described bySambrook et al., Molecular Cloning: A Laboratory Manual, New York: ColdSpring Harbor Press, 1989, and include the use of washing solution andhybridization conditions (e.g., temperature, ionic strength, and % SDS)less stringent that those described above. An example of moderatelystringent conditions is overnight incubation at 37° C. in a solutioncomprising: 20% formamide, 5×SSC (150 mM NaCl, 15 mM trisodium citrate),50 mM sodium phosphate (pH 7.6), 5×Denhardt's solution, 10% dextransulfate, and 20 mg/ml denatured sheared salmon sperm DNA, followed bywashing the filters in 1×SSC at about 37-50° C. The skilled artisan willrecognize how to adjust the temperature, ionic strength, etc. asnecessary to accommodate factors such as probe length and the like.

The practice of the present invention will employ, unless otherwiseindicated, conventional techniques of molecular biology (includingrecombinant techniques), microbiology, cell biology, and biochemistry,which are within the skill of the art. Such techniques are explainedfully in the literature, such as, Molecular Cloning: A LaboratoryManual, 2nd edition, Sambrook et al., 1989; Oligonucleotide Synthesis, MJ Gait, ed., 1984; Animal Cell Culture, R. I. Freshney, ed., 1987;Methods in Enzymology, Academic Press, Inc.; Handbook of ExperimentalImmunology, 4th edition, D. M. Weir & CC. Blackwell, eds., BlackwellScience Inc., 1987; Gene Transfer Vectors for Mammalian Cells, J. M.Miller & M. P. Calos, eds., 1987; Current Protocols in MolecularBiology, F. M. Ausubel et al., eds., 1987; and PCR: The Polymerase ChainReaction, Mullis et al., eds., 1994.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION

In colorectal cancer, discordant results have been reported forprognostic markers. The present invention discloses the use ofmicroarrays to reach a firmer conclusion, and to determine theprognostic role of specific prognostic signatures in colorectal cancer.The microarray-based studies shown herein indicate that particularprognostic signatures in colorectal cancer are associated with aprognosis. The invention can therefore be used to identify patients athigh risk of recurrence of cancer, or patients with a high likelihood ofrecovery.

The present invention provides for markers for the determination ofdisease prognosis, for example, the likelihood of recurrence of tumours,including colorectal tumours. Using the methods of the invention, it hasbeen found that numerous markers are associated with the prognosis ofcolorectal cancer, and can be used to predict disease outcome.Microarray analysis of samples taken from patients with various stagesof colorectal tumours has led to the surprising discovery that specificpatterns of marker expression are associated with prognosis of thecancer. The present invention therefore provides for a set of genes,outlined in Table 1 and Table 2, that are differentially expressed inrecurrent and non-recurrent colorectal cancers. The genes outlined inTable 1 and Table 2 provide for a set of colorectal cancer prognosticmakers (CCPMs).

A decrease in certain colorectal cancer prognostic markers (CCPMs), forexample, markers associated with immune responses, is indicative of aparticular prognosis. This can include increased likelihood of cancerrecurrence after standard treatment, especially for colorectal cancer.Conversely, an increase in other CCPMs is indicative of a particularprognosis. This can include disease progression or the increasedlikelihood of cancer recurrence, especially for colorectal cancer. Adecrease or increase in expression can be determined, for example, bycomparison of a test sample, e.g., patient's tumour sample, to areference sample, e.g., a sample associated with a known prognosis. Inparticular, one or more samples from patient(s) with non-recurrentcancer could be used as a reference sample.

For example, to obtain a prognosis, expression levels in a patient'ssample (e.g., tumour sample) can be compared to samples from patientswith a known outcome. If the patient's sample shows increased ordecreased expression of one or more CCPMs that compares to samples withgood outcome (no recurrence), then a positive prognosis, or recurrenceis unlikely, is implicated. If the patient's sample shows expression ofone or more CCPMs that is comparable to samples with poor outcome(recurrence), then a positive prognosis, or recurrence of the tumour islikely, is implicated.

As further examples, the expression levels of a prognostic signaturecomprising two or more CCPMS from a patient's sample (e.g., tumoursample) can be compared to samples of recurrent/non-recurrent cancer. Ifthe patient's sample shows increased or decreased expression of CCPMs bycomparison to samples of non-recurrent cancer, and/or comparableexpression to samples of recurrent cancer, then a negative prognosis isimplicated. If the patient's sample shows expression of CCPMs that iscomparable to samples of non-recurrent cancer, and/or lower or higherexpression than samples of recurrent cancer, then a positive prognosisis implicated.

As one approach, a prediction method can be applied to a panel ofmarkers, for example the panel of CCPMs outlined in Table 1 and Table 2,in order to generate a predictive model. This involves the generation ofa prognostic signature, comprising two or more CCPMs.

The disclosed CCPMs in Table 1 and Table 2 therefore provide a usefulset of markers to generate prediction signatures for determining theprognosis of cancer, and establishing a treatment regime, or treatmentmodality, specific for that tumour. In particular, a positive prognosiscan be used by a patient to decide to pursue standard or less invasivetreatment options. A negative prognosis can be used by a patient todecide to terminate treatment or to pursue highly aggressive orexperimental treatments. In addition, a patient can chose treatmentsbased on their impact on the expression of prognostic markers (e.g.,CCPMs).

Levels of CCPMs can be detected in tumour tissue, tissue proximal to thetumour, lymph node samples, blood samples, serum samples, urine samples,or faecal samples, using any suitable technique, and can include, but isnot limited to, oligonucleotide probes, quantitative PCR, or antibodiesraised against the markers. It will be appreciated that by analyzing thepresence and amounts of expression of a plurality of CCPMs in the formof prediction signatures, and constructing a prognostic signature (e.g.,as set forth in Tables 3, 4, 8A, 8B, and 9), the sensitivity andaccuracy of prognosis will be increased. Therefore, multiple markersaccording to the present invention can be used to determine theprognosis of a cancer.

The invention includes the use of archived paraffin-embedded biopsymaterial for assay of the markers in the set, and therefore iscompatible with the most widely available type of biopsy material. It isalso compatible with several different methods of tumour tissue harvest,for example, via core biopsy or fine needle aspiration. In certainaspects, RNA is isolated from a fixed, wax-embedded cancer tissuespecimen of the patient. Isolation may be performed by any techniqueknown in the art, for example from core biopsy tissue or fine needleaspirate cells.

In one aspect, the invention relates to a method of predicting aprognosis, e.g., the likelihood of long-term survival of a cancerpatient without the recurrence of cancer, comprising determining theexpression level of one or more prognostic markers or their expressionproducts in a sample obtained from the patient, normalized against theexpression level of other RNA transcripts or their products in thesample, or of a reference set of RNA transcripts or their expressionproducts. In specific aspects, the prognostic marker is one or moremarkers listed in Tables 1, 2, or 5, or is included as one or more ofthe prognostic signatures derived from the markers listed in Tables 1,2, and 5, or the prognostic signatures listed in Tables 3, 4, 8A, 8B, or9.

In further aspects, the expression levels of the prognostic markers ortheir expression products are determined, e.g., for the markers listedin Tables 1, 2, or 5, a prognostic signature derived from the markerslisted in Tables 1, 2, and 5, e.g., for the prognostic signatures listedin Tables 3, 4, 8A, 8B, or 9. In another aspect, the method comprisesthe determination of the expression levels of a full set of prognosismarkers or their expression products, e.g., for the markers listed inTables 1, 2, or 5, or, a prognostic signature derived from the markerslisted in Tables 1, 2, and 5, e.g., for the prognostic signatures listedin Tables 3, 4, 8A, 8B, or 9.

In an additional aspect, the invention relates to an array (e.g.,microarray) comprising polynucleotides hybridizing to two or moremarkers, e.g., for the markers listed in Tables 1, 2, and 5, or aprognostic signature derived from the markers listed in Tables 1, 2, and5, e.g., the prognostic signatures listed in Tables 3, 4, 8A, 8B, and 9.In particular aspects, the array comprises polynucleotides hybridizingto prognostic signature derived from the markers listed in Tables 1, 2,and 5, or e.g., for the prognostic signatures listed in Tables 3, 4, 8A,8B, or 9. In another specific aspect, the array comprisespolynucleotides hybridizing to the full set of markers, e.g., for themarkers listed in Tables 1, 2, or 5, or, e.g., for the prognosticsignatures listed in Tables 3, 4, 8A, 8B, or 9.

For these arrays, the polynucleotides can be cDNAs, or oligonucleotides,and the solid surface on which they are displayed can be glass, forexample. The polynucleotides can hybridize to one or more of the markersas disclosed herein, for example, to the full-length sequences, anycoding sequences, any fragments, or any complements thereof. Inparticular aspects, an increase or decrease in expression levels of oneor more CCPM indicates a decreased likelihood of long-term survival,e.g., due to cancer recurrence, while a lack of an increase or decreasein expression levels of one or more CCPM indicates an increasedlikelihood of long-term survival without cancer recurrence.

TABLE 1 Colorectal Cancer Predictive Markers (corresponding toAffymetrix GeneChip probes that show statistically significantdifferential expression, P < 0.05, as ascertained by BRB Array Tools)Expression Fold Difference Other (relapse/ Gene Affymetrix Probe Genbanknon- Symbol IDs Refseq Access. Gene Description Unigene Access. Access.relapse) ME2 210154_at, NM_002396 malic enzyme 2, Hs.233119 M55905, 0.74210153_s_at, NAD(+)-dependent, BC000147 209397_at mitochondrial STAT1AFFX- NM_007315, signal transducer Hs.470943 NM_007315, 0.58 HUMISGF3A/NM_139266 and activator of BC002704 M97935_MA_at, transcription 1, AFFX-91 kDa HUMISGF3A/ M97935_MB_at, AFFX- HUMISGF3A/ M97935_3_at,200887_s_at, AFFX- HUMISGF3A/ M97935_5_at, 209969_s_at CXCL10 204533_atNM_001565 chemokine (C—X—C Hs.413924 NM_001565 0.29 motif) ligand 10 FAS215719_x_at, NM_000043, Fas (TNF receptor Hs.244139 X83493, 0.68216252_x_at, NM_152871, superfamily, Z70519, 204780_s_at, NM_152872,member 6) AA164751, 204781_s_at NM_152873, NM_000043 NM_152874,NM_152875, NM_152876, NM_152877 SFRS2 200753_x_at, NM_003016 splicingfactor, Hs.73965 BE866585, 0.82 214882_s_at, arginine/serine-rich 2BG254869, 200754_x_at NM_003016 GUF1 218884_s_at NM_021927 GUF1 GTPaseHs.546419 NM_021927 0.71 homolog (S. cerevisiae) CXCL9 203915_atNM_002416 chemokine (C—X—C Hs.77367 NM_002416 0.33 motif) ligand 9 TYMS202589_at NM_001071 thymidylate Hs.369762 NM_001071 0.53 synthetaseSEC10L1 218748_s_at NM_006544 SEC10-like 1 (S. cerevisiae) Hs.365863NM_006544 0.76 PLK4 204887_s_at NM_014264 polo-like kinase 4 Hs.172052NM_014264 0.64 (Drosophila) MAP2K4 203265_s_at NM_003010mitogen-activated Hs.514681 AA810268 0.76 protein kinase kinase 4 EIF4E201435_s_at, NM_001968 eukaryotic Hs.249718 AW268640, 0.69 201436_attranslation initiation AI742789 factor 4E TLK1 210379_s_at NM_012290tousled-like kinase 1 Hs.470586 AF162666 0.59 CXCL11 210163_at,NM_005409 chemokine (C—X—C Hs.518814 AF030514, 0.15 211122_s_at motif)ligand 11 AF002985 PSME2 201762_s_at NM_002818 proteasome Hs.434081,NM_002818 0.68 (prosome, Hs.512410 macropain) activator subunit 2 (PA28beta) hCAP-D3 212789_at NM_015261 non-SMC condensin Hs.438550 AI7965810.83 II complex, subunit D3 MPP5 219321_at NM_022474 membrane protein,Hs.509699 NM_022474 0.74 palmitoylated 5 (MAGUK p55 subfamily member 5)DLGAP4 202570_s_at NM_014902, discs, large Hs.249600 BF346592 1.3NM_183006 (Drosophila) homolog-associated protein 4 WARS 200628_s_at,NM_004184, tryptophanyl-tRNA Hs.497599 M61715, 0.66 200629_at NM_173701,synthetase NM_004184 NM_213645, NM_213646 ARF6 203312_x_at NM_001663ADP-ribosylation Hs.525330 NM_001663 0.77 factor 6 PBK 219148_atNM_018492 PDZ binding kinase Hs.104741 NM_018492 0.41 GMFB 202543_s_atNM_004124 glia maturation Hs.151413 BC005359 0.66 factor, beta NDUFA9208969_at NM_005002 NADH Hs.75227 AF050641 0.77 dehydrogenase(ubiquinone) 1 alpha subcomplex, 9, 39 kDa CDC40 203377_s_at NM_015891cell division cycle Hs.428147 NM_015891 0.8 40 homolog (yeast) WHSC1209053_s_at, NM_007331, Wolf-Hirschhorn Hs.113876 BE793789, 0.75209054_s_at, NM_014919, syndrome candidate 1 AF083389, 209052_s_atNM_133330, BF111870 NM_133331, NM_133332, NM_133333, NM_133334,NM_133335, NM_133336 C1QBP 208910_s_at, NM_001212 complement Hs.555866L04636, 0.71 214214_s_at component 1, q AU151801 subcomponent bindingprotein RBM25 212031_at NM_021239 RNA binding motif Hs.531106 AV7573840.83 protein 25 SLC25A11 209003_at, NM_003562 solute carrier familyHs.184877 AF070548, 0.83 207088_s_at 25 (mitochondrial NM_003562carrier, oxoglutarate carrier), member 11 TK1 202338_at NM_003258thymidine kinase 1, Hs.515122 NM_003258 0.73 soluble ETNK1 222262_s_at,NM_018638 ethanolamine kinase 1 Hs.240056 AL137750, 0.66 219017_atNM_018638 KLHL24 221985_at NM_017644 kelch-like 24 Hs.407709 AW0067501.4 (Drosophila) AK2 212175_s_at, NM_001625, adenylate kinase 2Hs.470907 AL513611, 0.8 205996_s_at, NM_013411, NM_013411, 212174_atW02312 HNRPD 221481_x_at, NM_001003810, heterogeneous Hs.480073 D55672,0.8 209330_s_at, NM_002138, nuclear D55674, 200073_s_at NM_031369,ribonucleoprotein D M94630 NM_031370 (AU-rich element RNA bindingprotein 1, 37 kDa) GTPBP3 213835_x_at NM_032620, GTP binding proteinHs.334885 AL524262 0.87 NM_133644 3 (mitochondrial) PSAT1 220892_s_atNM_021154, phosphoserine Hs.494261 NM_021154 0.54 NM_058179aminotransferase 1 AP1G1 203350_at NM_001030007, adaptor-relatedHs.461253 NM_001128 0.89 NM_001128 protein complex 1, gamma 1 subunitSMCHD1 212577_at structural Hs.8118 AA868754 0.74 maintenance ofchromosomes flexible hinge domain containing 1 SLC4A4 210738_s_at,NM_003759 solute carrier family Hs.5462 AF011390, 0.7 203908_at, 4,sodium NM_003759, 211494_s_at, bicarbonate AF157492, 210739_x_atcotransporter, AF069510 member 4 RBMS3 206767_at NM_001003792, RNAbinding motif, Hs.221436 NM_014483 1.2 NM_001003793, single strandedNM_014483 interacting protein LARP4 214155_s_at NM_052879, Laribonucleoprotein Hs.26613 AI743740 0.66 NM_199188, domain family,NM_199190 member 4 FANCA 203805_s_at NM_000135, Fanconi anemia,Hs.284153 AW083279 0.78 NM_001018112 complementation group A SOS1212780_at NM_005633 son of sevenless Hs.278733 AA700167 0.84 homolog 1(Drosophila) IFT20 210312_s_at NM_174887 intraflagellar Hs.4187 BC0026401.2 transport 20 homolog (Chlamydomonas) NUP210 212316_at, NM_024923nucleoporin 210 kDa Hs.475525 AA502912, 0.78 220035_at, NM_024923,213947_s_at AI867102 IRF8 204057_at NM_002163 interferon regulatoryHs.137427 AI073984 0.75 factor 8 SGPP1 221268_s_at NM_030791sphingosine-1- Hs.24678 NM_030791 0.76 phosphate phosphatase 1 MAD2L1203362_s_at NM_002358 MAD2 mitotic arrest Hs.509523, NM_002358 0.7deficient-like 1 Hs.533185 (yeast) PAICS 201013_s_at, NM_006452phosphoribosylaminoimidazole Hs.518774 AA902652, 0.71 201014_s_atcarboxylase, NM_006452 phosphoribosylaminoimidazole succinocarboxamidesynthetase RPS2 217466_x_at NM_002952 ribosomal protein S2 Hs.356366,L48784 0.83 Hs.381079, Hs.498569, Hs.506997, Hs.556270 TMED5 202195_s_atNM_016040 transmembrane Hs.482873 NM_016040 0.86 emp24 protein transportdomain containing 5 GTSE1 204317_at, NM_016426 G-2 and S-phaseHs.386189, BF305380, 0.8 204318_s_at expressed 1 Hs.475140 NM_016426 DCK203302_at NM_000788 deoxycytidine kinase Hs.709 NM_000788 0.77DKFZp762E1312 218726_at NM_018410 hypothetical protein Hs.532968NM_018410 0.81 DKFZp762E1312 BAZ1A 217986_s_at NM_013448, bromodomainHs.509140 NM_013448 0.8 NM_182648 adjacent to zinc finger domain, 1AHIP2 202346_at NM_005339 huntingtin Hs.50308 NM_005339 0.78 interactingprotein 2 HNRPA3P1 206809_s_at heterogeneous Hs.524276 NM_005758 0.83nuclear ribonucleoprotein A3 pseudogene 1 CDC42BPA 214464_at NM_003607,CDC42 binding Hs.35433 NM_003607 1.4 NM_014826 protein kinase alpha(DMPK-like) P15RS 218209_s_at NM_018170 hypothetical protein Hs.464912NM_018170 0.79 FLJ10656 FLJ10534TSR1 218156_s_at NM_018128 TSR1, 20SrRNA Hs.388170 NM_018128 0.75 accumulation, homolog (S. cerevisiae) RRM1201476_s_at NM_001033 ribonucleotide Hs.383396 AI692974 0.76 reductaseM1 polypeptide USP4 202682_s_at NM_003363, ubiquitin specific Hs.77500NM_003363 1.2 NM_199443 peptidase 4 (proto- oncogene) ZNF304 207753_atNM_020657 zinc finger protein Hs.287374 NM_020657 1.3 304 CA2 209301_atNM_000067 carbonic anhydrase Hs.155097 M36532 0.25 II LOC92249212957_s_at hypothetical protein Hs.31532 AU154785 1.1 LOC92249 MARCH5218582_at NM_017824 membrane- Hs.549165 NM_017824 0.81 associated ringfinger (C3HC4) 5 TRMT5 221952_x_at NM_020810 TRM5 tRNA Hs.380159AB037814 0.81 methyltransferase 5 homolog (S. cerevisiae) PRDX3201619_at NM_006793, peroxiredoxin 3 Hs.523302 NM_006793 0.73 NM_014098RAP1GDS1 217457_s_at NM_021159 RAP1, GTP-GDP Hs.132858 X63465 0.82dissociation stimulator 1 NUMB 209073_s_at NM_001005743, numb homologHs.509909 AF015040 0.82 NM_001005744, (Drosophila) NM_001005745,NM_003744 KIF2 203087_s_at NM_004520 kinesin heavy chain Hs.533222NM_004520 0.72 member 2 ACADSB 205355_at NM_001609 acyl-Coenzyme AHs.81934 NM_001609 0.87 dehydrogenase, short/branched chain IBRDC3213038_at NM_153341 IBR domain Hs.546478 AL031602 0.88 containing 3 TES202719_s_at NM_015641, testis derived Hs.533391 BC001451 1.3 NM_152829transcript (3 LIM domains) YDD19 37079_at YDD19 protein Hs.525826 U823190.92 GZMB 210164_at NM_004131 granzyme B Hs.1051 J03189 0.66 (granzyme2, cytotoxic T- lymphocyte- associated serine esterase 1) LAP3217933_s_at NM_015907 leucine Hs.479264 NM_015907 0.67 aminopeptidase 3C17orf25 209092_s_at NM_016080 chromosome 17 Hs.279061 AF061730 0.72open reading frame 25 ZNF345 207236_at NM_003419 zinc finger proteinHs.362324 NM_003419 1.1 345 KITLG 207029_at, NM_000899, KIT ligandHs.1048 NM_000899, 0.75 211124_s_at NM_003994 AF119835 CAMSAP1L1212765_at NM_203459 calmodulin regulated Hs.23585 AB029001 1.3spectrin-associated protein 1-like 1 YTHDC2 205835_s_at, NM_022828 YTHdomain Hs.231942 AW975818, 0.84 205836_s_at containing 2 NM_022828 RABIF204477_at NM_002871 RAB interacting Hs.90875 U74324 1.2 factor SERBP1217725_x_at NM_001018067, SERPINE1 mRNA Hs.369448, NM_015640 0.81NM_001018068, binding protein 1 Hs.519284, NM_001018069, Hs.530412NM_015640 KPNB1 208975_s_at NM_002265 karyopherin Hs.532793 L38951 0.74(importin) beta 1 BRIP1 221703_at NM_032043 BRCA1 interacting Hs.532799AF360549 0.86 protein C-terminal helicase 1 IRF1 202531_at NM_002198interferon regulatory Hs.436061 NM_002198 0.62 factor 1 TIPIN 219258_atNM_017858 TIMELESS Hs.426696 NM_017858 0.73 interacting protein SPFH1202444_s_at NM_006459 SPFH domain Hs.150087 NM_006459 0.76 family,member 1 SFPQ 201586_s_at NM_005066 splicing factor Hs.355934 NM_0050660.83 proline/glutamine- rich (polypyrimidine tract binding proteinassociated) MGAT2 211061_s_at NM_001015883, mannosyl (alpha- Hs.93338BC006390 0.79 NM_002408 1,6-)-glycoprotein beta-1,2-N-acetylglucosaminyltransferase MCCC2 209624_s_at NM_022132methylcrotonoyl- Hs.167531 AB050049 0.6 Coenzyme A carboxylase 2 (beta)DDAH2 215537_x_at, NM_013974 dimethylarginine Hs.247362 AJ012008,AK026191 1.2 214909_s_at dimethylaminohydrolase 2 NP 201695_s_atNM_000270 nucleoside Hs.75514 NM_000270 0.79 phosphorylase CHEK1205393_s_at, NM_001274 CHK1 checkpoint Hs.24529 NM_001274 0.7 205394_athomolog (S. pombe) MYO1B 212365_at NM_012223 myosin IB Hs.439620BF215996 0.85 ATP5A1 213738_s_at NM_001001935, ATP synthase, H+Hs.298280, AI587323 0.82 NM_001001937, transporting, Hs.551998 NM_004046mitochondrial F1 complex, alpha subunit, isoform 1, cardiac muscle IL2RB205291_at NM_000878 interleukin 2 Hs.474787 NM_000878 0.73 receptor,beta RPL39 217665_at NM_001000 ribosomal protein Hs.558387 AA420614 1.3L39 (RPL39) CD59 212463_at NM_000611, CD59 antigen p18-20 Hs.278573BE379006 1.5 NM_203329, (antigen NM_203330, identified by NM_203331monoclonal antibodies 16.3A5, EJ16, EJ30, EL32 and G344) AMD1201196_s_at NM_001033059, adenosylmethionine Hs.159118 M21154 0.74NM_001634 decarboxylase 1 GGA2 210658_s_at NM_015044, golgi associated,Hs.460336 BC000284 0.82 NM_138640 gamma adaptin ear containing, ARFbinding protein 2 MCM6 201930_at NM_005915 MCM6 Hs.444118 NM_005915 0.75minichromosome maintenance deficient 6 (MIS5 homolog, S. pombe) (S.cerevisiae) SCC-112 213983_s_at, NM_015200 SCC-112 protein Hs.331431AW991219, 0.8 212138_at AK021757 BCL7C 219072_at NM_004765 B-cellHs.303197 NM_004765 1.2 CLL/lymphoma 7C HMGN2 208668_x_at NM_005517high-mobility group Hs.181163 BC003689 0.9 nucleosomal binding domain 2RBBP4 210371_s_at, NM_005610 retinoblastoma Hs.555890 BC003092, 0.8217301_x_at binding protein 4 X71810 KIAA0090 212396_s_at NM_015047KIAA0090 Hs.439200 AI143233 0.81 SYNPO 202796_at NM_007286 synaptopodinHs.435228 NM_007286 1.2 GPR161 214104_at NM_007369, G protein-coupledHs.271809 AI703188 1.5 NM_153832 receptor 161 TMEM113 215509_s_atNM_025222 transmembrane Hs.194110 AL137654 0.72 protein 113 SMC2L1204240_s_at NM_006444 SMC2 structural Hs.119023 NM_006444 0.65maintenance of chromosomes 2-like 1 (yeast) CCNA2 203418_at NM_001237cyclin A2 Hs.85137 NM_001237 0.6 VAPB 202549_at NM_004738 VAMP (vesicle-Hs.182625 AK025720 1.2 associated membrane protein)- associated proteinB and C EXOSC9 213226_at NM_005033 exosome component 9 Hs.91728 AI3463500.73 TRIM25 206911_at NM_005082 tripartite motif- Hs.528952, NM_0050820.88 containing 25 Hs.551516 SCYL2 221220_s_at NM_017988 SCY1-like 2 (S.cerevisiae) Hs.506481 NM_017988 0.85 RYK 214172_x_at NM_001005861, RYKreceptor-like Hs.245869 BG032035 1.2 NM_002958 tyrosine kinase MTHFD1202309_at NM_005956 methylenetetrahydro Hs.435974 NM_005956 0.74 folatedehydrogenase (NADP+ dependent) 1, methenyltetrahydrofolatecyclohydrolase, formyltetrahydrofolate synthetase RUNX1 211180_x_atNM_001001890, runt-related Hs.149261, D89788 1.1 NM_001754 transcriptionfactor 1 Hs.278446 (acute myeloid leukemia 1, aml1 oncogene) KPNA2201088_at, NM_002266 karyopherin alpha 2 Hs.159557, NM_002266, 0.77211762_s_at (RAG cohort 1, Hs.252712 BC005978 importin alpha 1) PSME1200814_at NM_006263, proteasome Hs.75348 NM_006263 0.76 NM_176783(prosome, macropain) activator subunit 1 (PA28 alpha) TACC3 218308_atNM_006342 transforming, acidic Hs.104019 NM_006342 0.78 coiled-coilcontaining protein 3 FEN1 204768_s_at NM_004111 flap structure-Hs.409065 NM_004111 0.73 specific endonuclease 1 GTF3C4 219198_atNM_012204 general transcription Hs.549088 NM_012204 0.87 factor IIIC,polypeptide 4, 90 kDa GEMIN4 217099_s_at NM_015721 gem (nuclearHs.499620 AF258545 0.76 organelle) associated protein 4 CTSS 202902_s_atNM_004079 cathepsin S Hs.181301 NM_004079 0.74 MCM2 202107_s_atNM_004526 MCM2 Hs.477481 NM_004526 0.71 minichromosome maintenancedeficient 2, mitotin (S. cerevisiae) GPHN 220773_s_at NM_001024218,gephyrin Hs.208765 NM_020806 0.67 NM_020806 NUP50 218295_s_at NM_007172,nucleoporin 50 kDa Hs.475103 NM_007172 0.78 NM_153645, NM_153684RANBP2L1 210676_x_at NM_005054, RAN binding Hs.469630 U64675 0.83NM_032260 protein 2-like 1 NR5A2 208337_s_at NM_003822, nuclear receptorHs.33446 NM_003822 0.77 NM_205860 subfamily 5, group A, member 2 PGD201118_at NM_002631 phosphogluconate Hs.464071 NM_002631 0.75dehydrogenase FUT4 209892_at, NM_002033 fucosyltransferase 4 Hs.390420AF305083, 0.78 209893_s_at (alpha (1,3) M58596 fucosyltransferase,myeloid-specific) RAB6A 201048_x_at NM_002869, RAB6A, member Hs.503222,NM_002869 0.81 NM_198896 RAS oncogene Hs.535586 family CCNT2 204645_atNM_001241, cyclin T2 Hs.292754 NM_001241 0.87 NM_058241 TFRC 207332_s_atNM_003234 transferrin receptor Hs.529618 NM_003234 0.63 (p90, CD71)BIRC5 202095_s_at NM_001012270, baculoviral IAP Hs.514527 NM_001168 0.7NM_001012271, repeat-containing 5 NM_001168 (survivin) PGGT1B 206288_atNM_005023 protein Hs.254006 NM_005023 0.8 geranylgeranyltransferase typeI, beta subunit USP14 201672_s_at NM_005151 ubiquitin specific Hs.464416NM_005151 0.81 peptidase 14 (tRNA- guanine transglycosylase) PURA204020_at NM_005859 purine-rich element Hs.443121 BF739943 1.2 bindingprotein A LMAN1 203293_s_at, NM_005570 lectin, mannose- Hs.465295NM_005570, 0.82 203294_s_at binding, 1 U09716 WDR45L 209076_s_atNM_019613 WDR45-like Hs.201390 BC000974 0.82 SGCD 213543_at NM_000337,sarcoglycan, delta Hs.387207 AA570453 1.2 NM_172244 (35 kDa dystrophin-associated glycoprotein) LRP8 205282_at NM_001018054, low densityHs.444637 NM_004631 0.78 NM_004631, lipoprotein receptor- NM_017522,related protein 8, NM_033300 apolipoprotein e receptor ITGA4 205885_s_atNM_000885 integrin, alpha 4 Hs.555880 L12002 0.74 (antigen CD49D, alpha4 subunit of VLA-4 receptor) BUB3 201458_s_at NM_001007793, BUB3 buddingHs.418533 NM_004725 0.79 NM_004725 uninhibited by benzimidazoles 3homolog (yeast) KIF18A 221258_s_at NM_031217 kinesin family Hs.301052NM_031217 0.83 member 18A FKBP9 212169_at NM_007270 FK506 bindingHs.103934 AL050187 1.2 protein 9, 63 kDa ATF6 217550_at NM_007348activating Hs.492740 AA576497 1.4 transcription factor 6 TNFRSF11A207037_at NM_003839 tumor necrosis Hs.204044 NM_003839 0.68 factorreceptor superfamily, member 11a, NFKB activator KIAA0841 213054_atKIAA0841 Hs.7426 AA845355 0.9 TGFB2 209909_s_at NM_003238 transforminggrowth Hs.133379 M19154 1.1 factor, beta 2 ITGB5 201125_s_at, NM_002213integrin, beta 5 Hs.13155 NM_002213, 1.2 201124_at, AL048423,214021_x_at AI335208 RABGEF1 218310_at NM_014504 RAB guanine Hs.530053NM_014504 1.2 nucleotide exchange factor (GEF) 1 PBX1 205253_at,NM_002585 pre-B-cell leukemia Hs.493096 NM_002585, 1.2 212148_attranscription factor 1 AL049381 ZNF148 203318_s_at NM_021964 zinc fingerprotein Hs.380334 NM_021964 1.2 148 (pHZ-52) ZWINT 204026_s_atNM_001005413, ZW10 interactor Hs.42650 NM_007057 0.66 NM_001005414,NM_007057, NM_032997 ZDHHC3 213675_at NM_016598 zinc finger, DHHC-Hs.61430 W61005 1.3 type containing 3 CDCA8 221520_s_at NM_018101 celldivision cycle Hs.524571 BC001651 0.76 associated 8 CUTL1 214743_atNM_001913, cut-like 1, CCAAT Hs.438974 BE046521 1.3 NM_181500,displacement protein NM_181552 (Drosophila) C18orf9 219311_at NM_024899chromosome 18 Hs.236940 NM_024899 0.73 open reading frame 9 TXNDC209476_at NM_030755 thioredoxin domain Hs.125221 AL080080 0.75containing POLE2 205909_at NM_002692 polymerase (DNA Hs.162777 NM_0026920.73 directed), epsilon 2 (p59 subunit) SPCS3 218817_at NM_021928 signalpeptidase Hs.42194 NM_021928 0.7 complex subunit 3 homolog (S.cerevisiae) CAND1 208839_s_at NM_018448 cullin-associated and Hs.546407AL136810 0.84 neddylation- dissociated 1 U2AF2 218381_s_at NM_001012478,U2 (RNU2) small Hs.528007 NM_007279 0.83 NM_007279 nuclear RNA auxiliaryfactor 2 WDHD1 204728_s_at NM_001008396, WD repeat and Hs.385998NM_007086 0.73 NM_007086 HMG-box DNA binding protein 1 HEM1 209734_atNM_005337 hematopoietic Hs.182014 BC001604 0.9 protein 1 RABEP1214552_s_at NM_004703 rabaptin, RAB Hs.551518 AF098638 0.84 GTPasebinding effector protein 1 SYDE1 44702_at NM_033025 synapse defective 1,Hs.528701 R77097 1.1 Rho GTPase, homolog 1 (C. elegans) WFDC1 219478_atNM_021197 WAP four-disulfide Hs.36688 NM_021197 1.2 core domain 1 TBX240560_at NM_005994 T-box 2 Hs.531085 U28049 1.1 GART 210005_atNM_000819, phosphoribosylglycinamide Hs.473648 D32051 0.84 NM_175085formyltransferase, phosphoribosylglycinamide synthetase,phosphoribosylaminoimidazole synthetase H2AFZ 213911_s_at, NM_002106 H2Ahistone family, Hs.119192 BF718636, 0.8 200853_at member Z NM_002106 CD7214551_s_at NM_006137 CD7 antigen (p41) Hs.36972 NM_006137 0.8 ELOVL6210868_s_at NM_024090 ELOVL family Hs.412939 BC001305 0.81 member 6,elongation of long chain fatty acids (FEN1/Elo2, SUR4/Elo3-like, yeast)CACNB3 34726_at NM_000725 calcium channel, Hs.250712 U07139 1.2voltage-dependent, beta 3 subunit TAP1 202307_s_at NM_000593 transporter1, ATP- Hs.352018 NM_000593 0.68 binding cassette, sub-family B(MDR/TAP) NUP98 210793_s_at NM_005387, nucleoporin 98 kDa Hs.524750U41815 0.75 NM_016320, NM_139131, NM_139132 CHAF1A 214426_x_at,NM_005483 chromatin assembly Hs.79018 BF062223, 0.83 203976_s_at factor1, subunit A NM_005483 (p150) EPAS1 200878_at NM_001430 endothelial PASHs.468410 AF052094 1.3 domain protein 1 RNGTT 204207_s_at NM_003800 RNAHs.127219 AB012142 0.8 guanylyltransferase and 5′-phosphatase KLF7204334_at NM_003709 Kruppel-like factor 7 Hs.471221 AA488672 1.1(ubiquitous) C4orf16 219023_at NM_018569 chromosome 4 open Hs.435991NM_018569 0.77 reading frame 16 YBX2 219704_at NM_015982 Y box bindingHs.380691 NM_015982 0.75 protein 2 IVD 216958_s_at NM_002225 isovalerylCoenzyme Hs.513646 AK022777 0.81 A dehydrogenase PEG3 209242_atNM_006210 paternally expressed 3 Hs.201776 AL042588 1.2 FBXL14 213145_atNM_152441 F-box and leucine- Hs.367956 BF001666 0.83 rich repeat protein14 TMEPAI 217875_s_at NM_020182, transmembrane, Hs.517155 NM_020182 1.4NM_199169, prostate androgen NM_199170, induced RNA NM_199171 RNF138218738_s_at NM_016271, ring finger protein Hs.302408, NM_016271 0.82NM_198128 138 Hs.501040 DNM1L 203105_s_at NM_005690, dynamin 1-likeHs.550499 NM_012062 0.87 NM_012062, NM_012063 LHCGR 215306_at NM_000233luteinizing Hs.468490 AL049443 1.3 hormone/choriogonadotropin receptorSOCS6 214462_at, NM_004232 suppressor of Hs.591068 NM_004232, 0.85206020_at cytokine signaling 6 NM_016387 (SOCS6) CEP350 213956_atNM_014810 centrosomal protein Hs.413045 AW299294 1.3 350 kDa PTGER3210374_x_at, NM_000957, prostaglandin E Hs.445000 D38300, 1.1210831_s_at NM_198712, receptor 3 (subtype L27489 NM_198713, EP3)NM_198714, NM_198715, NM_198716, NM_198717, NM_198718, NM_198719,NM_198720 M11S1 200723_s_at NM_005898, membrane Hs.471818 NM_005898 0.9NM_203364 component, chromosome 11, surface marker 1 RFC5 203210_s_atNM_007370, replication factor C Hs.506989 NM_007370 0.79 NM_181578(activator 1) 5, 36.5 kDa INDO 210029_at NM_002164 indoleamine-pyrroleHs.840 M34455 0.74 2,3 dioxygenase KIAA0286 212619_at NM_015257 NAHs.533787 AW205215 0.77 MOBK1B 201298_s_at NM_018221 MOB1, Mps OneHs.196437 BC003398 0.84 Binder kinase activator-like 1B (yeast) FLJ20273218035_s_at NM_019027 RNA-binding Hs.518727 NM_019027 0.73 proteinHADHSC 211569_s_at NM_005327 L-3-hydroxyacyl- Hs.438289 AF001903 0.62Coenzyme A dehydrogenase, short chain SSPN 204964_s_at NM_005086sarcospan (Kras Hs.183428 NM_005086 1.6 oncogene-associated gene) AP2B1200615_s_at NM_001030006, adaptor-related Hs.514819 AL567295 0.77NM_001282 protein complex 2, beta 1 subunit EIF4A1 201530_x_at,NM_001416 eukaryotic Hs.129673 NM_001416, 0.79 214805_at translationinitiation U79273 factor 4A, isoform 1 DEPDC1 220295_x_at NM_017779 DEPdomain Hs.445098 NM_017779 0.66 containing 1 AGPAT5 218096_at NM_0183611-acylglycerol-3- Hs.490899 NM_018361 0.68 phosphate O- acyltransferase5 (lysophosphatidic acid acyltransferase, epsilon) HNRPDL 201993_x_atNM_005463, heterogeneous Hs.527105 NM_005463 0.86 NM_031372 nuclearribonucleoprotein D- like GBP1 202270_at NM_002053 guanylate bindingHs.62661, NM_002053 0.61 protein 1, interferon- Hs.443527 inducible, 67kDa AMIGO2 222108_at NM_181847 adhesion molecule Hs.121520 AC004010 1.6with Ig-like domain 2 XPO7 208459_s_at NM_015024 exportin 7 Hs.172685NM_015024 0.78 PAWR 204005_s_at NM_002583 PRKC, apoptosis, Hs.406074NM_002583 0.71 WT1, regulator NARS 200027_at NM_004539 asparaginyl-tRNAHs.465224 NM_004539 0.84 synthetase CENPA 204962_s_at NM_001809centromere protein Hs.1594 NM_001809 0.69 A, 17 kDa KIF15 219306_atNM_020242 kinesin family Hs.307529 NM_020242 0.78 member 15 ZNF518204291_at NM_014803 zinc finger protein Hs.147895 NM_014803 0.88 518 LPP202821_s_at NM_005578 LIM domain Hs.444362 AL044018 1.3 containingpreferred translocation partner in lipoma BRRN1 212949_at NM_015341barren homolog Hs.308045 D38553 0.76 (Drosophila) C5orf4 48031_r_atNM_016348, chromosome 5 open Hs.519694 H93077 1.2 NM_032385 readingframe 4 UBAP1 46270_at NM_016525 ubiquitin associated Hs.268963 AL0394471.1 protein 1 SH3GLB1 209090_s_at NM_016009 SH3-domain GRB2- Hs.136309AL049597 1.2 like endophilin B1 CDKN1C 213182_x_at NM_000076cyclin-dependent Hs.106070 R78668 1.4 kinase inhibitor 1C (p57, Kip2)MCM10 220651_s_at NM_018518, MCM10 Hs.198363 NM_018518 0.74 NM_182751minichromosome maintenance deficient 10 (S. cerevisiae) KIAA0265209254_at NM_014997 KIAA0265 protein Hs.520710 AI808625 1.2 BUB1209642_at NM_004336 BUB1 budding Hs.469649 AF043294 0.68 uninhibited bybenzimidazoles 1 homolog (yeast) LGALS3BP 200923_at NM_005567 lectin,galactoside- Hs.514535 NM_005567 0.8 binding, soluble, 3 binding proteinNCAPD2 201774_s_at NM_014865 non-SMC condensin Hs.5719 AK022511 0.73 Icomplex, subunit D2 CD86 205686_s_at NM_006889, CD86 antigen Hs.171182NM_006889 0.88 NM_175862 (CD28 antigen ligand 2, B7-2 antigen) C16orf30219315_s_at NM_024600 chromosome 16 Hs.459652 NM_024600 1.2 open readingframe 30 RBBP8 203344_s_at NM_002894, retinoblastoma Hs.546282 NM_0028940.79 NM_203291, binding protein 8 NM_203292 FEM1C 213341_at NM_020177fem-1 homolog c Hs.47367 AI862658 0.82 (C. elegans) NUP160 214962_s_atNM_015231 nucleoporin 160 kDa Hs.372099 AK026236 0.84 VAMP4 213480_atNM_003762, vesicle-associated Hs.6651 AF052100 1.1 NM_201994 membraneprotein 4 C9orf76 218979_at NM_024945 chromosome 9 open Hs.284137NM_024945 0.8 reading frame 76 DHX15 201386_s_at NM_001358 DEAH(Asp-Glu- Hs.5683 AF279891 0.83 Ala-His) box polypeptide 15 RIG221127_s_at regulated in glioma Hs.292156 NM_006394 1.2 HBP1 209102_s_atNM_012257 HMG-box Hs.162032 AF019214 1.2 transcription factor 1 ABCE1201873_s_at, NM_002940 ATP-binding Hs.12013 NM_002940, 0.79 201872_s_atcassette, sub-family, AI002002 E (OABP), member 1 PPA2 220741_s_atNM_006903, pyrophosphatase Hs.480452 NM_006903 0.81 NM_176866,(inorganic) 2 NM_176867, NM_176869 CPD 201942_s_at NM_001304carboxypeptidase D Hs.446079 D85390 0.68 KIAA0828 215672_s_at NM_015328adenosylhomocysteinase 3 Hs.195058 AK025372 0.73 K- 211058_x_atNM_006082 alpha tubulin Hs.524390 BC006379 0.85 ALPHA-1 RNMT 202684_s_atNM_003799 RNA (guanine-7-) Hs.8086 AB020966 0.9 methyltransferase MIS12221559_s_at NM_024039 MIS12 homolog Hs.267194 BC000229 0.8 (yeast) AURKB209464_at NM_004217 aurora kinase B Hs.442658 AB011446 0.71 FAM64A221591_s_at NM_019013 family with Hs.404323 BC005004 0.8 sequencesimilarity 64, member A TAP2 204770_at NM_000544, transporter 2, ATP-Hs.502 NM_000544 0.82 NM_018833 binding cassette, sub-family B (MDR/TAP)PCDHGC3 205717_x_at NM_002588, protocadherin Hs.368160 NM_002588 1.2NM_032402, gamma subfamily C, 3 NM_032403 AVEN 219366_at NM_020371apoptosis, caspase Hs.555966 NM_020371 1.1 activation inhibitor HMGB2208808_s_at NM_002129 high-mobility group Hs.434953 BC000903 0.76 box 2CDC2 203214_x_at NM_001786, cell division cycle 2, Hs.334562 NM_0017860.72 NM_033379 G1 to S and G2 to M RIF1 214700_x_at NM_018151 RAP1interacting Hs.536537 AK000323 0.84 factor homolog (yeast) TCF7L2216511_s_at NM_030756 transcription factor Hs.501080 AJ270770 0.8 7-like2 (T-cell specific, HMG-box) KIF11 204444_at NM_004523 kinesin familyHs.8878 NM_004523 0.68 member 11 TTC19 217964_at NM_017775tetratricopeptide Hs.462316 NM_017775 0.67 repeat domain 19 MDS032221706_s_at NM_018467 uncharacterized Hs.16187 BC006005 1.2hematopoietic stem/progenitor cells protein MDS032 PSMA3 201532_atNM_002788, proteasome Hs.531089 NM_002788 0.76 NM_152132 (prosome,macropain) subunit, alpha type, 3 PDGFA 205463_s_at platelet-derivedHs.376032, NM_002607 1.3 growth factor alpha Hs.521331 polypeptideGTF2H2 221540_x_at NM_001515 general transcription Hs.191356, AF0788470.86 factor IIH, Hs.398348 polypeptide 2, 44 kDa CXCL13 205242_atNM_006419 chemokine (C—X—C Hs.100431 NM_006419 0.36 motif) ligand 13 (B-cell chemoattractant) FOXM1 202580_x_at NM_021953, forkhead box M1Hs.239 NM_021953 0.7 NM_202002, NM_202003 YARS 212048_s_at NM_003680tyrosyl-tRNA Hs.213264 AW245400 0.87 synthetase SE57-1 220180_atNM_025214 coiled-coil domain Hs.120790 NM_025214 0.77 containing 68CLCA4 220026_at NM_012128 chloride channel, Hs.546343 NM_012128 0.64calcium activated, family member 4 MCAM 211340_s_at NM_006500 melanomacell Hs.511397 M28882 1.2 adhesion molecule PBXIP1 214177_s_at NM_020524pre-B-cell leukemia Hs.505806 AI935162 1.2 transcription factorinteracting protein 1 PPM1D 204566_at NM_003620 protein phosphataseHs.286073 NM_003620 0.88 1D magnesium- dependent, delta isoform FLJ22471218175_at NM_025140 NA Hs.114111 NM_025140 1.2 ZBTB20 205383_s_atNM_015642 zinc finger and BTB Hs.122417 NM_015642 1.4 domain containing20 RRM2 209773_s_at NM_001034 ribonucleotide Hs.226390 BC001886 0.69reductase M2 polypeptide

TABLE 2 Markers with expression correlating to that of the 22 genes fromNZ signature. Expression Fold Difference (relapse/ Affymetrix RefseqUnigene Genbank non- Gene Symbol Probe IDs Access Gene DescriptionAccess Access relapse) CCL5 1405_i_at, NM_002985 chemokine (C-C motif)Hs.514821 M21121, 0.69 204655_at ligand 5 NM_002985 SFRS10 200893_atNM_004593 splicing factor, Hs.533122 NM_004593 0.96 arginine/serine-rich10 (transformer 2 homolog, Drosophila) HLA-E 200904_at NM_005516 majorhistocompatibility Hs.381008 X56841 1 complex, class I, E K-ALPHA-1201090_x_at NM_006082 alpha tubulin Hs.524390 NM_006082 0.87 PSMA5201274_at NM_002790 proteasome (prosome, Hs.485246 NM_002790 0.95macropain) subunit, alpha type, 5 TOP2A 201292_at NM_001067topoisomerase (DNA) II Hs.156346 AL561834 0.77 alpha 170 kDa EBNA1BP2201323_at NM_006824 EBNA1 binding protein 2 Hs.346868 NM_006824 0.98SNRPC 201342_at NM_003093 small nuclear Hs.1063 NM_003093 1ribonucleoprotein polypeptide C UBE2L6 201649_at NM_004223,ubiquitin-conjugating Hs.425777 NM_004223 0.75 NM_198183 enzyme E2L 6LAPTM5 201720_s_at NM_006762 lysosomal associated Hs.371021 AI5890860.89 multispanning membrane protein 5 CTSL 202087_s_at NM_001912,cathepsin L Hs.418123 NM_001912 0.97 NM_145918 GBP1 202269_x_atNM_002053 guanylate binding protein Hs.62661, BC002666 0.69 1,interferon-inducible, Hs.443527 67 kDa TNFAIP2 202510_s_at NM_006291tumor necrosis factor, Hs.525607 NM_006291 0.91 alpha-induced protein 2CCNB2 202705_at NM_004701 cyclin B2 Hs.194698 NM_004701 0.83 GBP2202748_at NM_004120 guanylate binding protein Hs.386567 NM_004120 0.872, interferon-inducible CDC20 202870_s_at NM_001255 CDC20 cell divisionHs.524947 NM_001255 0.78 cycle 20 homolog (S. cerevisiae) HAT1 203138_atNM_001033085, histone acetyltransferase 1 Hs.470611 NM_003642 0.95NM_003642 SPAG5 203145_at NM_006461 sperm associated antigen 5 Hs.514033NM_006461 0.87 RFC5 203209_at NM_007370, replication factor C Hs.506989BC001866 0.79 NM_181578 (activator 1) 5, 36.5 kDa MYCBP 203360_s_atNM_012333 c-myc binding protein Hs.370040 D50692 1 BUB1B 203755_atNM_001211 BUB1 budding Hs.36708 NM_001211 0.85 uninhibited bybenzimidazoles 1 homolog beta (yeast) SLA 203761_at NM_006748Src-like-adaptor Hs.75367 NM_006748 0.97 VRK1 203856_at NM_003384vaccinia related kinase 1 Hs.422662 NM_003384 0.72 PIK3CD 203879_atNM_005026 phosphoinositide-3- Hs.518451 U86453 0.99 kinase, catalytic,delta polypeptide HLA-DMB 203932_at NM_002118 major histocompatibilityHs.1162 NM_002118 0.82 complex, class II, DM beta TRIP13 204033_atNM_004237 thyroid hormone receptor Hs.436187 NM_004237 0.78 interactor13 RARRES3 204070_at NM_004585 retinoic acid receptor Hs.17466 NM_0045850.96 responder (tazarotene induced) 3 CKS2 204170_s_at NM_001827 CDC28protein kinase Hs.83758 NM_001827 0.8 regulatory subunit 2 APOBEC3G204205_at NM_021822 apolipoprotein B mRNA Hs.474853 NM_021822 0.74editing enzyme, catalytic polypeptide-like 3G PSMB9 204279_at NM_002800,proteasome (prosome, Hs.381081 NM_002800 0.63 NM_148954 macropain)subunit, beta type, 9 (large multifunctional peptidase 2) FUSIP1204299_at NM_054016 FUS interacting protein Hs.3530 NM_021993 0.9(serine/arginine-rich) 1 SELL 204563_at NM_000655 selectin L (lymphocyteHs.82848 NM_000655 0.88 adhesion molecule 1) DKK1 204602_at NM_012242dickkopf homolog 1 Hs.40499 NM_012242 0.95 (Xenopus laevis) KIF23204709_s_at NM_004856, kinesin family member Hs.270845 NM_004856 0.9NM_138555 23 TTK 204822_at NM_003318 TTK protein kinase Hs.169840NM_003318 0.8 ECGF1 204858_s_at NM_001953 endothelial cell growthHs.546251 NM_001953 0.85 factor 1 (platelet-derived) LCP2 205269_at,NM_005565 lymphocyte cytosolic Hs.304475 AI123251, 0.91 205270_s_atprotein 2 (SH2 domain NM_005565 containing leukocyte protein of 76 kDa)BTN2A2 205298_s_at NM_006995, butyrophilin, subfamily Hs.373938 W587570.94 NM_181531 2, member A2 BMP5 205431_s_at NM_021073 bonemorphogenetic Hs.296648 NM_021073 0.9 protein 5 GZMA 205488_at NM_006144granzyme A (granzyme Hs.90708 NM_006144 0.68 1, cytotoxic T-lymphocyte-associated serine esterase 3) SMURF2 205596_s_at NM_022739SMAD specific E3 Hs.515011 AY014180 1 ubiquitin protein ligase 2 CD8A205758_at NM_001768, CD8 antigen, alpha Hs.85258 AW006735 0.78 NM_171827polypeptide (p32) CD2 205831_at NM_001767 CD2 antigen (p50), sheepHs.523500 NM_001767 0.87 red blood cell receptor JAK2 205842_s_atNM_004972 Janus kinase 2 (a protein Hs.434374 AF001362 0.86 tyrosinekinase) UBD 205890_s_at NM_006398 ubiquitin D Hs.44532 NM_006398 0.41ADH1C 206262_at NM_000669 alcohol dehydrogenase Hs.2523 NM_000669 0.331C (class I), gamma polypeptide AIM2 206513_at NM_004833 absent inmelanoma 2 Hs.281898 NM_004833 0.91 SI 206664_at NM_001041sucrase-isomaltase Hs.429596 NM_001041 0.39 (alpha-glucosidase) NAT2206797_at NM_000015 N-acetyltransferase 2 Hs.2 NM_000015 0.82 (arylamineN- acetyltransferase) SP110 208012_x_at NM_004509, SP110 nuclear bodyHs.145150 NM_004509 0.95 NM_004510, protein NM_080424 PRDX1 208680_atNM_002574, peroxiredoxin 1 Hs.180909 L19184 1 NM_181696, NM_181697 PSMA6208805_at NM_002791 proteasome (prosome, Hs.446260 BC002979 0.87macropain) subunit, alpha type, 6 IFI16 208966_x_at NM_005531interferon, gamma- Hs.380250 AF208043 1.2 inducible protein 16 PPIG208995_s_at NM_004792 peptidyl-prolyl isomerase Hs.470544 U40763 0.98 G(cyclophilin G) KIF2C 209408_at, NM_006845 kinesin family memberHs.69360 U63743, 0.75 211519_s_at 2C AY026505 APOL1 209546_s_atNM_003661, apolipoprotein L, 1 Hs.114309 AF323540 0.98 NM_145343,NM_145344 CD74 209619_at NM_001025158, CD74 antigen (invariant Hs.436568K01144 0.76 NM_001025159, polypeptide of major NM_004355histocompatibility complex, class II antigen- associated) HMMR209709_s_at NM_012484, hyaluronan-mediated Hs.72550 U29343 0.84NM_012485 motility receptor (RHAMM) CDKN3 209714_s_at NM_005192cyclin-dependent kinase Hs.84113 AF213033 0.71 inhibitor 3 (CDK2-associated dual specificity phosphatase) BUB3 209974_s_at NM_001007793,BUB3 budding Hs.418533 AF047473 0.84 NM_004725 uninhibited bybenzimidazoles 3 homolog (yeast) SOCS1 210001_s_at NM_003745 suppressorof cytokine Hs.50640 AB005043 0.93 signaling 1 CD3Z 210031_at NM_000734,CD3Z antigen, zeta Hs.156445 J04132 0.87 NM_198053 polypeptide (TiT3complex) CACYBP 210691_s_at NM_001007214, calcyclin binding proteinHs.508524 AF275803 0.97 NM_014412 HLA-DRA 210982_s_at NM_019111 majorhistocompatibility Hs.520048 M60333 0.74 complex, class II, DR alphaNEK2 211080_s_at NM_002497 NIMA (never in mitosis Hs.153704 Z25425 0.77gene a)-related kinase 2 NF2 211091_s_at NM_000268, neurofibromin 2Hs.187898 AF122828 0.96 NM_016418, (bilateral acoustic NM_181825,neuroma) NM_181826, NM_181827, NM_181828, NM_181829, NM_181830,NM_181831, NM_181832, NM_181833, NM_181834, NM_181835 FYB 211795_s_atNM_001465, FYN binding protein Hs.370503 AF198052 0.83 NM_199335(FYB-120/130) HLA-DPA1 211991_s_at NM_033554 major histocompatibilityHs.347270 M27487 0.75 complex, class II, DP alpha 1 PTPRC 212587_s_at,NM_002838, protein tyrosine Hs.192039 AI809341, 0.77 212588_atNM_080921, phosphatase, receptor Y00062 NM_080922, type, C NM_080923 SP3213168_at NM_001017371, Sp3 transcription factor Hs.531587 AU145005 0.98NM_003111 ITGAL 213475_s_at NM_002209 integrin, alpha L (antigenHs.174103 AC002310 0.85 CD11A (p180), lymphocyte function- associatedantigen 1, alpha polypeptide) RAC2 213603_s_at NM_002872 ras-related C3botulinum Hs.517601 BE138888 0.92 toxin substrate 2 (rho family, smallGTP binding protein Rac2) DNA2L 213647_at DNA2 DNA replication Hs.532446D42046 0.87 helicase 2-like (yeast) TRAF3IP3 213888_s_at NM_025228 TRAF3interacting Hs.147434 AL022398 0.86 protein 3 NKG7 213915_at NM_005601natural killer cell group 7 Hs.10306 NM_005601 0.72 sequence SFRS7214141_x_at NM_001031684, splicing factor, Hs.309090 BF033354 0.88NM_006276 arginine/serine-rich 7, 35 kDa ZG16 214142_at NM_152338zymogen granule protein Hs.184507 AI732905 0.18 16 PRF1 214617_atNM_005041 perforin 1 (pore forming Hs.2200 AI445650 0.81 protein) CCNB1214710_s_at NM_031966 cyclin B1 Hs.23960 BE407516 0.63 KIAA0907214995_s_at NM_014949 KIAA0907 Hs.24656 BF508948 0.82 GTSE1 215942_s_atNM_016426 G-2 and S-phase Hs.386189, BF973178 0.86 expressed 1 Hs.475140HMGB3 216548_x_at NM_005342 high-mobility group box 3 Hs.19114 AL0497090.97 HLA-DMA 217478_s_at NM_006120 major histocompatibility Hs.351279X76775 0.8 complex, class II, DM alpha C20orf45 217851_s_at NM_016045chromosome 20 open Hs.3945 NM_016045 1.1 reading frame 45 MRPL42217919_s_at NM_014050, mitochondrial ribosomal Hs.199579 BE782148 0.79NM_172177, protein L42 NM_172178 NUSAP1 218039_at, NM_016359, nucleolarand spindle Hs.511093 NM_016359, 0.92 219978_s_at NM_018454 associatedprotein 1 NM_018454 TMEM48 218073_s_at NM_018087 transmembrane protein48 Hs.476525 NM_018087 0.71 DHX40 218277_s_at NM_024612 DEAH(Asp-Glu-Ala- Hs.29403 NM_024612 1.1 His) box polypeptide 40 NFS1218455_at NM_021100, NFS1 nitrogen fixation 1 Hs.194692 NM_021100 1NM_181679 (S. cerevisiae) C10orf3 218542_at NM_018131 chromosome 10 openHs.14559 NM_018131 0.77 reading frame 3 NCAPG 218663_at NM_022346non-SMC condensin I Hs.446201, NM_022346 0.73 complex, subunit GHs.479270 FBXO5 218875_s_at NM_012177 F-box protein 5 Hs.520506NM_012177 0.89 SLAMF8 219385_at NM_020125 SLAM family member 8 Hs.438683NM_020125 0.94 CENPN 219555_s_at NM_018455 centromere protein NHs.283532 NM_018455 0.81 ATP13A3 219558_at ATPase type 13A3 Hs.529609NM_024524 0.75 ECT2 219787_s_at NM_018098 epithelial cell Hs.518299NM_018098 0.75 transforming sequence 2 oncogene ASPM 219918_s_atNM_018136 asp (abnormal spindle)- Hs.121028 NM_018123 0.89 like,microcephaly associated (Drosophila) ZC3HAV1 220104_at NM_020119, zincfinger CCCH-type, Hs.133512 NM_020119 0.93 NM_024625 antiviral 1 CLEC2D220132_s_at NM_001004419, C-type lectin superfamily Hs.268326 NM_0132690.91 NM_001004420, 2, member D NM_013269 MS4A12 220834_at NM_017716membrane-spanning 4- Hs.272789 NM_017716 0.5 domains, subfamily A,member 12 C1orf112 220840_s_at NM_018186 chromosome 1 open Hs.443551NM_018186 0.96 reading frame 112 TPRT 220865_s_at NM_014317trans-prenyltransferase Hs.555924 NM_014317 0.92 APOL3 221087_s_atNM_014349, apolipoprotein L, 3 Hs.474737 NM_014349 0.84 NM_030644,NM_145639, NM_145640, NM_145641, NM_145642 C14orf156 221434_s_atNM_031210 chromosome 14 open Hs.324521 NM_031210 0.9 reading frame 156YTHDF3 221749_at NM_152758 YTH domain family, Hs.491861 AU157915 0.95member 3 LOC146909 222039_at hypothetical protein Hs.135094 AA2927890.83 LOC146909 TRAFD1 35254_at NM_006700 TRAF-type zinc finger Hs.5148AB007447 0.98 domain containing 1 ESPL1 38158_at NM_012291 extra spindlepoles like 1 Hs.153479 D79987 0.87 (S. cerevisiae) BTN3A3 38241_atNM_006994, butyrophilin, subfamily Hs.167741 U90548 0.9 NM_197974 3,member A3

General Approaches to Prognostic Marker Detection

The following approaches are non-limiting methods that can be used todetect the proliferation markers, including CCPM family members:microarray approaches using oligonucleotide probes selective for a CCPM;real-time qPCR on tumour samples using CCPM specific primers and probes;real-time qPCR on lymph node, blood, serum, faecal, or urine samplesusing CCPM specific primers and probes; enzyme-linked immunologicalassays (ELISA); immunohistochemistry using anti-marker antibodies; andanalysis of array or qPCR data using computers.

Other useful methods include northern blotting and in situ hybridization(Parker and Barnes, Methods in Molecular Biology 106: 247-283 (1999));RNase protection assays (Hod, BioTechniques 13: 852-854 (1992)); reversetranscription polymerase chain reaction (RT-PCR; Weis et al., Trends inGenetics 8: 263-264 (1992)); serial analysis of gene expression (SAGE;Velculescu et al., Science 270: 484-487 (1995); and Velculescu et al.,Cell 88: 243-51 (1997)), MassARRAY technology (Sequenom, San Diego,Calif.), and gene expression analysis by massively parallel signaturesequencing (MPSS; Brenner et al., Nature Biotechnology 18: 630-634(2000)). Alternatively, antibodies may be employed that can recognizespecific complexes, including DNA duplexes, RNA duplexes, and DNA-RNAhybrid duplexes or DNA-polypeptide duplexes.

Primary data can be collected and fold change analysis can be performed,for example, by comparison of marker expression levels in tumour tissueand non-tumour tissue; by comparison of marker expression levels tolevels determined in recurring tumours and non-recurring tumours; bycomparison of marker expression levels to levels determined in tumourswith or without metastasis; by comparison of marker expression levels tolevels determined in differently staged tumours; or by comparison ofmarker expression levels to levels determined in cells with differentlevels of proliferation. A negative or positive prognosis is determinedbased on this analysis. Further analysis of tumour marker expressionincludes matching those markers exhibiting increased or decreasedexpression with expression profiles of known colorectal tumours toprovide a prognosis.

A threshold for concluding that expression is increased will bedependent on the particular marker and also the particular predictivemodel that is to be applied. The threshold is generally set to achievethe highest sensitivity and selectivity with the lowest error rate,although variations may be desirable for a particular clinicalsituation. The desired threshold is determined by analysing a populationof sufficient size taking into account the statistical variability ofany predictive model and is calculated from the size of the sample usedto produce the predictive model. The same applies for the determinationof a threshold for concluding that expression is decreased. It can beappreciated that other thresholds, or methods for establishing athreshold, for concluding that increased or decreased expression hasoccurred can be selected without departing from the scope of thisinvention.

It is also possible that a prediction model may produce as it's output anumerical value, for example a score, likelihood value or probability.In these instances, it is possible to apply thresholds to the resultsproduced by prediction models, and in these cases similar principlesapply as those used to set thresholds for expression values.

Once the expression level, or output of a prediction model, of apredictive signature in a tumour sample has been obtained, thelikelihood of the cancer recurring can then be determined.

From the markers identified, prognostic signatures comprising one ormore CCPMs can be used to determine the prognosis of a cancer, bycomparing the expression level of the one or more markers to thedisclosed prognostic signature. By comparing the expression of one ormore of the CCPMs in a tumour sample with the disclosed prognosticsignature, the likelihood of the cancer recurring can be determined. Thecomparison of expression levels of the prognostic signature to establisha prognosis can be done by applying a predictive model as describedpreviously.

Determining the likelihood of the cancer recurring is of great value tothe medical practitioner. A high likelihood of re-occurrence means thata longer or higher dose treatment should be given, and the patientshould be more closely monitored for signs of recurrence of the cancer.An accurate prognosis is also of benefit to the patient. It allows thepatient, along with their partners, family, and friends to also makedecisions about treatment, as well as decisions about their future andlifestyle changes. Therefore, the invention also provides for a methodestablishing a treatment regime for a particular cancer based on theprognosis established by matching the expression of the markers in atumour sample with the differential expression signature.

It will be appreciated that the marker selection, or construction of aprognostic signature, does not have to be restricted to the CCPMsdisclosed in Tables 1, 2, or 5, herein, or the prognostic signaturesdisclosed in Tables 3, 4, 8A, 8B, and 9, but could involve the use ofone or more CCPMs from the disclosed signatures, or a new signature maybe established using CCPMs selected from the disclosed marker lists. Therequirement of any signature is that it predicts the likelihood ofrecurrence with enough accuracy to assist a medical practitioner toestablish a treatment regime.

Reverse Transcription PCR (RT-PCR)

Of the techniques listed above, the most sensitive and most flexiblequantitative method is RT-PCR, which can be used to compare RNA levelsin different sample populations, in normal and tumour tissues, with orwithout drug treatment, to characterize patterns of expression, todiscriminate between closely related RNAs, and to analyze RNA structure.

For RT-PCR, the first step is the isolation of RNA from a target sample.The starting material is typically total RNA isolated from human tumoursor tumour cell lines, and corresponding normal tissues or cell lines,respectively. RNA can be isolated from a variety of samples, such astumour samples from breast, lung, colon (e.g., large bowel or smallbowel), colorectal, gastric, esophageal, anal, rectal, prostate, brain,liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, etc.,tissues, from primary tumours, or tumour cell lines, and from pooledsamples from healthy donors. If the source of RNA is a tumour, RNA canbe extracted, for example, from frozen or archived paraffin-embedded andfixed (e.g., formalin-fixed) tissue samples.

The first step in gene expression profiling by RT-PCR is the reversetranscription of the RNA template into cDNA, followed by its exponentialamplification in a PCR reaction. The two most commonly used reversetranscriptases are avian myeloblastosis virus reverse transcriptase(AMV-RT) and Moloney murine leukaemia virus reverse transcriptase(MMLV-RT). The reverse transcription step is typically primed usingspecific primers, random hexamers, or oligo-dT primers, depending on thecircumstances and the goal of expression profiling. For example,extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit(Perkin Elmer, CA, USA), following the manufacturer's instructions. Thederived cDNA can then be used as a template in the subsequent PCRreaction.

Although the PCR step can use a variety of thermostable DNA-dependentDNA polymerases, it typically employs the Taq DNA polymerase, which hasa 5′-3′ nuclease activity but lacks a 3′-5′ proofreading endonucleaseactivity. Thus, TaqMan (q) PCR typically utilizes the 5′ nucleaseactivity of Taq or Tth polymerase to hydrolyze a hybridization probebound to its target amplicon, but any enzyme with equivalent 5′ nucleaseactivity can be used.

Two oligonucleotide primers are used to generate an amplicon typical ofa PCR reaction. A third oligonucleotide, or probe, is designed to detectnucleotide sequence located between the two PCR primers. The probe isnon-extendible by Taq DNA polymerase enzyme, and is labeled with areporter fluorescent dye and a quencher fluorescent dye. Anylaser-induced emission from the reporter dye is quenched by thequenching dye when the two dyes are located close together as they areon the probe. During the amplification reaction, the Taq DNA polymeraseenzyme cleaves the probe in a template-dependent manner. The resultantprobe fragments disassociate in solution, and signal from the releasedreporter dye is free from the quenching effect of the secondfluorophore. One molecule of reporter dye is liberated for each newmolecule synthesized, and detection of the unquenched reporter dyeprovides the basis for quantitative interpretation of the data.

TaqMan RT-PCR can be performed using commercially available equipment,such as, for example, ABI PRISM 7700 Sequence Detection System(Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA), orLightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In apreferred embodiment, the 5′ nuclease procedure is run on a real-timequantitative PCR device such as the ABI PRISM 7700tam Sequence DetectionSystem. The system consists of a thermocycler, laser, charge-coupleddevice (CCD), camera, and computer. The system amplifies samples in a96-well format on a thermocycler. During amplification, laser-inducedfluorescent signal is collected in real-time through fibre optics cablesfor all 96 wells, and detected at the CCD. The system includes softwarefor running the instrument and for analyzing the data.

5′ nuclease assay data are initially expressed as Ct, or the thresholdcycle. As discussed above, fluorescence values are recorded during everycycle and represent the amount of product amplified to that point in theamplification reaction. The point when the fluorescent signal is firstrecorded as statistically significant is the threshold cycle.

To minimize errors and the effect of sample-to-sample variation, RT-PCRis usually performed using an internal standard. The ideal internalstandard is expressed at a constant level among different tissues, andis unaffected by the experimental treatment. RNAs most frequently usedto normalize patterns of gene expression are mRNAs for the housekeepinggenes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and-actin.

Real-Time Quantitative PCR (qPCR)

A more recent variation of the RT-PCR technique is the real timequantitative PCR, which measures PCR product accumulation through adual-labeled fluorigenic probe (i.e., TaqMan probe). Real time PCR iscompatible both with quantitative competitive PCR and with quantitativecomparative PCR. The former uses an internal competitor for each targetsequence for normalization, while the latter uses a normalization genecontained within the sample, or a housekeeping gene for RT-PCR. Furtherdetails are provided, e.g., by Held et al., Genome Research 6: 986-994(1996).

Expression levels can be determined using fixed, paraffin-embeddedtissues as the RNA source. According to one aspect of the presentinvention, PCR primers and probes are designed based upon intronsequences present in the gene to be amplified. In this embodiment, thefirst step in the primer/probe design is the delineation of intronsequences within the genes. This can be done by publicly availablesoftware, such as the DNA BLAT software developed by Kent, W. J., GenomeRes. 12 (4): 656-64 (2002), or by the BLAST software including itsvariations. Subsequent steps follow well established methods of PCRprimer and probe design.

In order to avoid non-specific signals, it is useful to mask repetitivesequences within the introns when designing the primers and probes. Thiscan be easily accomplished by using the Repeat Masker program availableon-line through the Baylor College of Medicine, which screens DNAsequences against a library of repetitive elements and returns a querysequence in which the repetitive elements are masked. The maskedsequences can then be used to design primer and probe sequences usingany commercially or otherwise publicly available primer/probe designpackages, such as Primer Express (Applied Biosystems); MGBassay-by-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J.Skaletsky (2000) Primer3 on the WWW for general users and for biologistprogrammers in: Krawetz S, Misener S (eds) Bioinformatics Methods andProtocols: Methods in Molecular Biology. Humana Press, Totowa, N.J., pp365-386).

The most important factors considered in PCR primer design includeprimer length, melting temperature (T_(m)), and G/C content,specificity, complementary primer sequences, and 3′ end sequence. Ingeneral, optimal PCR primers are generally 17-30 bases in length, andcontain about 20-80%, such as, for example, about 50-60% G+C bases.Melting temperatures between 50 and 80° C., e.g., about 50 to 70° C.,are typically preferred. For further guidelines for PCR primer and probedesign see, e.g., Dieffenbach, C. W. et al., General Concepts for PCRPrimer Design in: PCR Primer, A Laboratory Manual, Cold Spring HarborLaboratory Press, New York, 1995, pp. 133-155; Innis and Gelfand,Optimization of PCRs in: PCR Protocols, A Guide to Methods andApplications, CRC Press, London, 1994, pp. 5-11; and Plasterer, T. N.Primerselect: Primer and probe design. Methods Mol. Biol. 70: 520-527(1997), the entire disclosures of which are hereby expresslyincorporated by reference.

Microarray Analysis

Differential expression can also be identified, or confirmed using themicroarray technique. Thus, the expression profile of CCPMs can bemeasured in either fresh or paraffin-embedded tumour tissue, usingmicroarray technology. In this method, polynucleotide sequences ofinterest (including cDNAs and oligonucleotides) are plated, or arrayed,on a microchip substrate. The arrayed sequences (i.e., capture probes)are then hybridized with specific polynucleotides from cells or tissuesof interest (i.e., targets). Just as in the RT-PCR method, the source ofRNA typically is total RNA isolated from human tumours or tumour celllines, and corresponding normal tissues or cell lines. Thus RNA can beisolated from a variety of primary tumours or tumour cell lines. If thesource of RNA is a primary tumour, RNA can be extracted, for example,from frozen or archived formalin fixed paraffin-embedded (FFPE) tissuesamples and fixed (e.g., formalin-fixed) tissue samples, which areroutinely prepared and preserved in everyday clinical practice.

In a specific embodiment of the microarray technique, PCR amplifiedinserts of cDNA clones are applied to a substrate. The substrate caninclude up to 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, or 75nucleotide sequences. In other aspects, the substrate can include atleast 10,000 nucleotide sequences. The microarrayed sequences,immobilized on the microchip, are suitable for hybridization understringent conditions. As other embodiments, the targets for themicroarrays can be at least 50, 100, 200, 400, 500, 1000, or 2000 basesin length; or 50-100, 100-200, 100-500, 100-1000, 100-2000, or 500-5000bases in length. As further embodiments, the capture probes for themicroarrays can be at least 10, 15, 20, 25, 50, 75, 80, or 100 bases inlength; or 10-15, 10-20, 10-25, 10-50, 10-75, 10-80, or 20-80 bases inlength.

Fluorescently labeled cDNA probes may be generated through incorporationof fluorescent nucleotides by reverse transcription of RNA extractedfrom tissues of interest. Labeled cDNA probes applied to the chiphybridize with specificity to each spot of DNA on the array. Afterstringent washing to remove non-specifically bound probes, the chip isscanned by confocal laser microscopy or by another detection method,such as a CCD camera. Quantitation of hybridization of each arrayedelement allows for assessment of corresponding mRNA abundance. With dualcolour fluorescence, separately labeled cDNA probes generated from twosources of RNA are hybridized pairwise to the array. The relativeabundance of the transcripts from the two sources corresponding to eachspecified gene is thus determined simultaneously. An exemplary protocolfor this is described in detail in Example 4.

The miniaturized scale of the hybridization affords a convenient andrapid evaluation of the expression pattern for large numbers of genes.Such methods have been shown to have the sensitivity required to detectrare transcripts, which are expressed at a few copies per cell, and toreproducibly detect at least approximately two-fold differences in theexpression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93 (2):106-149 (1996)). Microarray analysis can be performed by commerciallyavailable equipment, following manufacturer's protocols, such as byusing the Affymetrix GenChip technology, IIlumina microarray technologyor Incyte's microarray technology. The development of microarray methodsfor large-scale analysis of gene expression makes it possible to searchsystematically for molecular markers of cancer classification andoutcome prediction in a variety of tumour types.

RNA Isolation, Purification, and Amplification

General methods for mRNA extraction are well known in the art and aredisclosed in standard textbooks of molecular biology, including Ausubelet al., Current Protocols of Molecular Biology, John Wiley and Sons(1997). Methods for RNA extraction from paraffin embedded tissues aredisclosed, for example, in Rupp and Locker, Lab Invest. 56: A67 (1987),and De Sandres et al., BioTechniques 18: 42044 (1995). In particular,RNA isolation can be performed using purification kit, buffer set, andprotease from commercial manufacturers, such as Qiagen, according to themanufacturer's instructions. For example, total RNA from cells inculture can be isolated using Qiagen RNeasy mini-columns. Othercommercially available RNA isolation kits include MasterPure CompleteDNA and RNA Purification Kit (EPICENTRE (D, Madison, Wis.), and ParaffinBlock RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samplescan be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumourcan be isolated, for example, by cesium chloride density gradientcentrifugation.

The steps of a representative protocol for profiling gene expressionusing fixed, paraffin-embedded tissues as the RNA source, including mRNAisolation, purification, primer extension and amplification are given invarious published journal articles (for example: T. E. Godfrey et al. J.Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol.158: 419-29 (2001)). Briefly, a representative process starts withcutting about 10 μm thick sections of paraffin-embedded tumour tissuesamples. The RNA is then extracted, and protein and DNA are removed.After analysis of the RNA concentration, RNA repair and/or amplificationsteps may be included, if necessary, and RNA is reverse transcribedusing gene specific promoters followed by RT-PCR. Finally, the data areanalyzed to identify the best treatment option(s) available to thepatient on the basis of the characteristic gene expression patternidentified in the tumour sample examined.

Immunohistochemistry and Proteomics

Immunohistochemistry methods are also suitable for detecting theexpression levels of the proliferation markers of the present invention.Thus, antibodies or antisera, preferably polyclonal antisera, and mostpreferably monoclonal antibodies specific for each marker, are used todetect expression. The antibodies can be detected by direct labeling ofthe antibodies themselves, for example, with radioactive labels,fluorescent labels, hapten labels such as, biotin, or an enzyme such ashorse radish peroxidase or alkaline phosphatase. Alternatively,unlabeled primary antibody is used in conjunction with a labeledsecondary antibody, comprising antisera, polyclonal antisera or amonoclonal antibody specific for the primary antibody.Immunohistochemistry protocols and kits are well known in the art andare commercially available.

Proteomics can be used to analyze the polypeptides present in a sample(e.g., tissue, organism, or cell culture) at a certain point of time. Inparticular, proteomic techniques can be used to assess the globalchanges of polypeptide expression in a sample (also referred to asexpression proteomics). Proteomic analysis typically includes: (1)separation of individual polypeptides in a sample by 2-D gelelectrophoresis (2-D PAGE); (2) identification of the individualpolypeptides recovered from the gel, e.g., by mass spectrometry orN-terminal sequencing, and (3) analysis of the data usingbioinformatics. Proteomics methods are valuable supplements to othermethods of gene expression profiling, and can be used, alone or incombination with other methods, to detect the products of theproliferation markers of the present invention.

Once the expression level of one or more prognostic markers in a tumoursample has been assessed the likelihood of the cancer recurring can thenbe determined. The inventors have identified a number of markers thatare differentially expressed in non-recurring colorectal cancerscompared to recurring colorectal cancers in patient data sets. Themarkers are set out in Tables 1, 2, and 9, in the examples below.

Selection of Differentially Expressed Genes.

An early approach to the selection of genes deemed significant involvedsimply looking at the “fold change” of a given gene between the twogroups of interest. While this approach hones in on genes that seem tochange the most spectacularly, consideration of basic statistics leadsone to realize that if the variance (or noise level) is quite high (asis often seen in microarray experiments), then seemingly largefold-change can happen frequently by chance alone.

Microarray experiments, such as those described here, typically involvethe simultaneous measurement of thousands of genes. If one is comparingthe expression levels for a particular gene between two groups (forexample recurrent and non-recurrent tumours), the typical tests forsignificance (such as the t-test) are not adequate. This is because, inan ensemble of thousands of experiments (in this context each geneconstitutes an “experiment”), the probability of at least one experimentpassing the usual criteria for significance by chance alone isessentially unity. In a test for significance, one typically calculatesthe probability that the “null hypothesis” is correct. In the case ofcomparing two groups, the null hypothesis is that there is no differencebetween the two groups. If a statistical test produces a probability forthe null hypothesis below some threshold (usually 0.05 or 0.01), it isstated that we can reject the null hypothesis, and accept the hypothesisthat the two groups are significantly different. Clearly, in such atest, a rejection of the null hypothesis by chance alone could beexpected 1 in 20 times (or 1 in 100). The use of t-tests, or othersimilar statistical tests for significance, fail in the context ofmicroarrays, producing far too many false positives (or type I errors)

In this type of situation, where one is testing multiple hypotheses atthe same time, one applies typical multiple comparison procedures, suchas the Bonferroni Method (43). However such tests are too conservativefor most microarray experiments, resulting in too many false negative(type II) errors.

A more recent approach is to do away with attempting to apply aprobability for a given test being significant, and establish a meansfor selecting a subset of experiments, such that the expected proportionof Type I errors (or false discovery rate; 47) is controlled for. It isthis approach that has been used in this investigation, through variousimplementations, namely the methods provided with BRB Array Tools (48),and the limma (11,42) package of Bioconductor (that uses the Rstatistical environment; 10,39).

General Methodology for Data Mining: Generation of Prognostic Signatures

Data Mining is the term used to describe the extraction of “knowledge”,in other words the “know-how”, or predictive ability from (usually)large volumes of data (the dataset). This is the approach used in thisstudy to generate prognostic signatures. In the case of this study the“know-how” is the ability to accurately predict prognosis from a givenset of gene expression measurements, or “signature” (as describedgenerally in this section and in more detail in the examples section).

The specific details used for the methods used in this study aredescribed in Examples 17-20. However, application of any of the datamining methods (both those described in the Examples, and thosedescribed here) can follow this general protocol.

Data mining (49), and the related topic machine learning (40) is acomplex, repetitive mathematical task that involves the use of one ormore appropriate computer software packages (see below). The use ofsoftware is advantageous on the one hand, in that one does not need tobe completely familiar with the intricacies of the theory behind eachtechnique in order to successfully use data mining techniques, providedthat one adheres to the correct methodology. The disadvantage is thatthe application of data mining can often be viewed as a “black box”: oneinserts the data and receives the answer. How this is achieved is oftenmasked from the end-user (this is the case for many of the techniquesdescribed, and can often influence the statistical method chosen fordata mining. For example, neural networks and support vector machineshave a particularly complex implementation that makes it very difficultfor the end user to extract out the “rules” used to produce thedecision. On the other hand, k-nearest neighbours and lineardiscriminant analysis have a very transparent process for decisionmaking that is not hidden from the user.

There are two types of approach used in data mining: supervised andunsupervised approaches. In the supervised approach, the informationthat is being linked to the data is known, such as categorical data(e.g. recurrent vs. non recurrent tumours). What is required is theability to link the observed response (e.g. recurrence vs.non-recurrence) to the input variables. In the unsupervised approach,the classes within the dataset are not known in advance, and data miningmethodology is employed to attempt to find the classes or structurewithin the dataset.

In the present example the supervised approach was used and is discussedin detail here, although it will be appreciated that any of the othertechniques could be used.

The overall protocol involves the following steps:

-   -   Data representation. This involves transformation of the data        into a form that is most likely to work successfully with the        chosen data mining technique. In where the data is numerical,        such as in this study where the data being investigated        represents relative levels of gene expression, this is fairly        simple. If the data covers a large dynamic range (i.e. many        orders of magnitude) often the log of the data is taken. If the        data covers many measurements of separate samples on separate        days by separate investigators, particular care has to be taken        to ensure systematic error is minimised. The minimisation of        systematic error (i.e. errors resulting from protocol        differences, machine differences, operator differences and other        quantifiable factors) is the process referred to here as        “normalisation”.    -   Feature Selection. Typically the dataset contains many more data        elements than would be practical to measure on a day-to-day        basis, and additionally many elements that do not provide the        information needed to produce a prediction model. The actual        ability of a prediction model to describe a dataset is derived        from some subset of the full dimensionality of the dataset.        These dimensions the most important components (or features) of        the dataset. Note in the context of microarray data, the        dimensions of the dataset are the individual genes. Feature        selection, in the context described here, involves finding those        genes which are most “differentially expressed”. In a more        general sense, it involves those groups which pass some        statistical test for significance, i.e. is the level of a        particular variable consistently higher or lower in one or other        of the groups being investigated. Sometimes the features are        those variables (or dimensions) which exhibit the greatest        variance. The application of feature selection is completely        independent of the method used to create a prediction model, and        involves a great deal of experimentation to achieve the desired        results. Within this invention, the selection of significant        genes, and those which correlated with the earlier successful        model (the NZ classifier), entailed feature selection. In        addition, methods of data reduction (such as principal component        analysis) can be applied to the dataset.    -   Training. Once the classes (e.g. recurrence/non-recurrence) and        the features of the dataset have been established, and the data        is represented in a form that is acceptable as input for data        mining, the reduced dataset (as described by the features) is        applied to the prediction model of choice. The input for this        model is usually in the form a multi-dimensional numerical        input, (known as a vector), with associated output information        (a class label or a response). In the training process, selected        data is input into the prediction model, either sequentially (in        techniques such as neural networks) or as a whole (in techniques        that apply some form of regression, such as linear models,        linear discriminant analysis, support vector machines). In some        instances (e.g. k-nearest neighbours) the dataset (or subset of        the dataset obtained after feature selection) is itself the        model. As discussed, effective models can be established with        minimal understanding of the detailed mathematics, through the        use of various software packages where the parameters of the        model have been pre-determined by expert analysts as most likely        to lead to successful results.    -   Validation. This is a key component of the data-mining protocol,        and the incorrect application of this frequently leads to        errors. Portions of the dataset are to be set aside, apart from        feature selection and training, to test the success of the        prediction model. Furthermore, if the results of validation are        used to effect feature selection and training of the model, then        one obtains a further validation set to test the model before it        is applied to real-life situations. If this process is not        strictly adhered to the model is likely to fail in real-world        situations. The methods of validation are described in more        detail below.    -   Application. Once the model has been constructed, and validated,        it must be packaged in some way as it is accessible to end        users. This often involves implementation of some form a        spreadsheet application, into which the model has been imbedded,        scripting of a statistical software package, or refactoring of        the model into a hard-coded application by information        technology staff.

Examples of software packages that are frequently used are:

-   -   Spreadsheet plugins, obtained from multiple vendors.    -   The R statistical environment.    -   The commercial packages MatLab, S-plus, SAS, SPSS, STATA.    -   Free open-source software such as Octave (a MatLab clone)    -   many and varied C++ libraries, which can be used to implement        prediction models in a commercial, closed-source setting.

Examples of Data Mining Methods.

The methods can be by first performing the step of data mining process(above), and then applying the appropriate known software packages.Further description of the process of data mining is described in detailin many extremely well-written texts.(49)

-   -   Linear models (49, 50): The data is treated as the input of a        linear regression model, of which the class labels or responses        variables are the output. Class labels, or other categorical        data, must be transformed into numerical values (usually        integer). In generalised linear models, the class labels or        response variables are not themselves linearly related to the        input data, but are transformed through the use of a “link        function”. Logistic regression is the most common form of        generalized linear model.    -   Linear Discriminant analysis (49, 51, 52). Provided the data is        linearly separable (i.e. the groups or classes of data can be        separated by a hyperplane, which is an n-dimensional extension        of a threshold), this technique can be applied. A combination of        variables is used to separate the classes, such that the between        group variance is maximised, and the within-group variance is        minimised. The byproduct of this is the formation of a        classification rule. Application of this rule to samples of        unknown class allows predictions or classification of class        membership to be made for that sample. There are variations of        linear discriminant analysis such as nearest shrunken centroids        which are commonly used for microarray analysis.    -   Support vector machines (53): A collection of variables is used        in conjunction with a collection of weights to determine a model        that maximizes the separation between classes in terms of those        weighted variables. Application of this model to a sample then        produces a classification or prediction of class membership for        that sample.    -   Neural networks (52): The data is treated as input into a        network of nodes, which superficially resemble biological        neurons, which apply the input from all the nodes to which they        are connected, and transform the input into an output. Commonly,        neural networks use the “multiply and sum” algorithm, to        transform the inputs from multiple connected input nodes into a        single output. A node may not necessarily produce an output        unless the inputs to that node exceed a certain threshold. Each        node has as its input the output from several other nodes, with        the final output node usually being linked to a categorical        variable. The number of nodes, and the topology of the nodes can        be varied in almost infinite ways, providing for the ability to        classify extremely noisy data that may not be possible to        categorize in other ways. The most common implementation of        neural networks is the multi-layer perceptron.    -   Classification and regression trees (54): In these. variables        are used to define a hierarchy of rules that can be followed in        a stepwise manner to determine the class of a sample. The        typical process creates a set of rules which lead to a specific        class output, or a specific statement of the inability to        discriminate. A example classification tree is an implementation        of an algorithm such as:

if gene A> x and gene Y > x and gene Z = z then   class A else if geneA= q   then  class B

-   -   Nearest neighbour methods (51, 52). Predictions or        classifications are made by comparing a sample (of unknown        class) to those around it (or known class), with closeness        defined by a distance function. It is possible to define many        different distance functions. Commonly used distance functions        are the Euclidean distance (an extension of the Pythagorean        distance, as in triangulation, to n-dimensions), various forms        of correlation (including Pearson Correlation co-efficient).        There are also transformation functions that convert data points        that would not normally be interconnected by a meaningful        distance metric into euclidean space, so that Euclidean distance        can then be applied (e.g. Mahalanobis distance). Although the        distance metric can be quite complex, the basic premise of        k-nearest neighbours is quite simple, essentially being a        restatement of “find the k-data vectors that are most similar to        the unknown input, find out which class they correspond to, and        vote as to which class the unknown input is”.    -   Other methods:        -   Bayesian networks. A directed acyclic graph is used to            represent a collection of variables in conjunction with            their joint probability distribution, which is then used to            determine the probability of class membership for a sample.        -   Independent components analysis, in which independent            signals (e.g., class membership) re isolated (into            components) from a collection of variables. These components            can then be used to produce a classification or prediction            of class membership for a sample.    -   Ensemble learning methods in which a collection of prediction        methods are combined to produce a joint classification or        prediction of class membership for a sample

There are many variations of these methodologies that can be explored(49), and many new methodologies are constantly being defined anddeveloped. It will be appreciated that any one of these methodologiescan be applied in order to obtain an acceptable result. Particular caremust be taken to avoid overfitting, by ensuring that all results aretested via a comprehensive validation scheme.

Validation

Application of any of the prediction methods described involves bothtraining and cross-validation (43, 55) before the method can be appliedto new datasets (such as data from a clinical trial). Training involvestaking a subset of the dataset of interest (in this case gene expressionmeasurements from colorectal tumours), such that it is stratified acrossthe classes that are being tested for (in this case recurrent andnon-recurrent tumours). This training set is used to generate aprediction model (defined above), which is tested on the remainder ofthe data (the testing set).

It is possible to alter the parameters of the prediction model so as toobtain better performance in the testing set, however, this can lead tothe situation known as overfitting, where the prediction model works onthe training dataset but not on any external dataset. In order tocircumvent this, the process of validation is followed. There are twomajor types of validation typically applied, the first (hold-outvalidation) involves partitioning the dataset into three groups:testing, training, and validation. The validation set has no input intothe training process whatsoever, so that any adjustment of parameters orother refinements must take place during application to the testing set(but not the validation set). The second major type is cross-validation,which can be applied in several different ways, described below.

There are two main sub-types of cross-validation: K-foldcross-validation, and leave-one-out cross-validation

K-fold cross-validation: The dataset is divided into K subsamples, eachsubsample containing approximately the same proportions of the classgroups as the original. In each round of validation, one of the Ksubsamples is set aside, and training is accomplished using theremainder of the dataset. The effectiveness of the training for thatround is gauged by how correctly the classification of the left-outgroup is. This procedure is repeated K-times, and the overalleffectiveness ascertained by comparison of the predicted class with theknown class.

Leave-one-out cross-validation: A commonly used variation of K-foldcross validation, in which K=n, where n is the number of samples.

Combinations of CCPMS, such as those described above in Tables 1 and 2,can be used to construct predictive models for prognosis.

Prognostic Signatures

Prognostic signatures, comprising one or more of these markers, can beused to determine the outcome of a patient, through application of oneor more predictive models derived from the signature. In particular, aclinician or researcher can determine the differential expression (e.g.,increased or decreased expression) of the one or more markers in thesignature, apply a predictive model, and thereby predict the negativeprognosis, e.g., likelihood of disease relapse, of a patient, oralternatively the likelihood of a positive prognosis (continuedremission).

A set of prognostic signatures have been developed. In the firstinstance, there are two signatures developed by cross-comparison ofpredictive ability between two datasets: the set of microarrayexperiments encompassing the German colorectal cancer samples, and theset of microarray experiments encompassing the New Zealand samples(discussed in example 6). In the second instance there has been anexhaustive statistical search for effective signatures based solely onthe German dataset (discussed in example 17).

As described in Example 6 below, a prognostic signature comprising 19genes has been established from a set of colorectal samples from Germany(Table 4). Another prognostic signature, of 22 genes, has also beenestablished from samples of colorectal tumours from patients in NewZealand (Table 3). By obtaining a patient sample (e.g., tumour sample),and matching the expression levels of one or more markers in the sampleto the differential expression profile, the likelihood of the cancerrecurring can be determined.

TABLE 3 New Zealand prognostic signature WDR44 WD repeat domain 44 0.81Hs.98510 NM_019045 RBMS1 rna binding motif, single stranded 1.27Hs.470412 NM_016836 interacting protein 1, isoform d SACM1L Ras-GTPaseactivating protein 0.84 Hs.156509 NM_014016 SH3 domain-binding protein 2SOAT1 sterol o-acyltransferase acyl- 1.21 Hs.496383 NM_003101 coenzymea: cholesterol acyltransferase 1 PBK pdz-binding kinase 0.76 Hs.104741NM_018492 G3BP2 ras-gtpase activating protein 0.86 Hs.303676 NM_012297sh3 domain-binding protein 2 ZBTB20 zinc finger and BTB domain 1.2Hs.477166 NM_015642 containing 20 ZNF410 zinc finger protein 410 0.84Hs.270869 NM_021188 COMMD2 COMM domain containing 2 1.09 Hs.591315NM_016094 PSMC1 proteasome (prosome, macropain) 0.79 Hs.356654 NM_00280226s subunit, atpase, 1 COX10 COX10 homolog, cytochrome c 0.9 Hs.462278NM_001303 oxidase assembly protein, heme A: farnesyltransferase (yeast)GTF3C5 general transcription factor 0.84 Hs.495417 NM_012087 iiic,polypeptide 5 (63 kd) HMMR hyaluronan-mediated motility 0.78 Hs.72550NM_012485 receptor (rhamm) UBE2L3 ubiquitin-conjugating enzyme e2l 30.83 Hs.108104 NM_003347 GNAS gnas complex locus 1.26 Hs.125898NM_000516 PPP2R2A protein phosphatase 2 (formerly 2a), 0.91 Hs.146339NM_002717 regulatory subunit b (pr 52), alpha isoform RNASE2ribonuclease, rnase a family, 2 0.83 Hs.728 NM_002934 (liver,eosinophil-derived neurotoxin) SCOC short coiled-coil protein 0.78Hs.480815 NM_032547 PSMD9 proteasome (prosome, macropain) 0.89 Hs.131151NM_002813 26s subunit, non-atpase, 9 EIF3S7 eukaryotic translationinitiation 0.85 Hs.55682 NM_003753 factor 3, subunit 7 (zeta, 66/67 kd)ATP2B4 ATPase, Ca++ transporting, 1.11 Hs.343522 NM_001001396 plasmamembrane 4 NM_001684 ABCC9 atp-binding cassette, sub-family c, 0.9Hs.446050 NM_020298 member 9, isoform sur2a-delta-14

TABLE 4 German prognostic signature Expression fold difference Gene(relapse/ UniGene GenBank Symbol Gene Description non-relapse) ClusterAcc. No. CXCL10 Chemokine (C-X-C motif) 0.87 Hs.413924 NM_001565 ligand10 FAS FAS (TNF receptor 0.9 Hs.244139 NM_000043 superfamily, member 6)NM_152871 NM_152872 NM_152873 NM_152874 NM_152875 NM_152876 NM_152877CXCL9 chemokine (C-X-C motif) 0.87 Hs.77367 NM_002416 ligand 9 TLK1tousled-like kinase 1 0.91 Hs.470586 NM_012290 CXCL11 chemokine (C-X-Cmotif) 0.75 Hs.518814 NM_005409 ligand 11 PBK T-LAK cell-originated 0.86Hs.104741 NM_018492 protein kinase PSAT1 phosphoserine 0.91 Hs.494261NM_021154 aminotransferase 1 MAD2L1 MAD2 mitotic arrest 0.89 Hs.533185NM_002358 deficient-like 1 (yeast) CA2 carbonic anhydrase II 0.84Hs.155097 NM_000067 GZMB granzyme B (granzyme 2, 0.9 Hs.1051 NM_004131cytotoxic T-lymphocyte- associated serine esterase 1) SLC4A4 solutecarrier family 4, 0.86 Hs.5462 NM_003759 sodium bicarbonatecotransporter, member 4 DLG7 discs, large homolog 7 0.89 Hs.77695NM_014750 (Drosophila) TNFRSF11A tumor necrosis factor receptor 0.9Hs.204044 NM_003839 superfamily, member 11a, activator of NFKB KITLG KITligand 0.91 Hs.1048 NM_000899 INDO indoleamine-pyrrole 2,3 0.91 Hs.840NM_002164 dioxygenase GBP1 guanylate binding protein 1, 0.9 Hs.62661NM_002053 interferon-inducible, 67 kDa CXCL13 chemokine (C-X-C motif)0.86 Hs.100431 NM_006419 ligand 13 (B-cell chemoattractant) CLCA4chloride channel, calcium 0.84 Hs.546343 NM_012128 activated, familymember 4 PCP4 Purkinje cell protein 4 1.14 Hs.80296 NM_006198

TABLE 5 Immune response genes Expression fold difference Gene (relapse/UniGene GenBank Symbol Gene Description non-relapse) Cluster Acc. No.CXCL9 chemokine (C-X-C motif) 0.87 Hs.77367 NM_002416 ligand 9 CXCL10Chemokine (C-X-C motif) 0.87 Hs.413924 NM_001565 ligand 10 CXCL11chemokine (C-X-C motif) 0.75 Hs.518814 AF030514 ligand 11 CXCL13chemokine (C-X-C motif) 0.86 Hs.100431 NM_006419 ligand 13 (B-cellchemoattractant) PBK T-LAK cell-originated 0.86 Hs.104741 NM_018492protein kinase INDO indoleamine-pyrrole 2,3 0.91 Hs.840 M34455dioxygenase GBP1 guanylate binding protein 1, 0.9 Hs.62661 NM_002053interferon-inducible, 67 kDa GZMB granzyme B (granzyme 2, 0.9 Hs.1051J03189 cytotoxic T-lymphocyte- associated serine esterase 1) KITLG KITligand 0.91 Hs.1048 NM_000899 TNFRSF11A tumor necrosis factor receptor0.9 Hs.204044 NM_003839 superfamily, member 11a, activator of NFKB FASFAS (TNF receptor 0.9 Hs.244139 Z70519 superfamily, member 6)

In certain aspects, this invention provides methods for determining theprognosis of a cancer, comprising: (a) providing a sample of the cancer;(b) detecting the expression level of a CCPM family member in saidsample; and (c) determining the prognosis of the cancer. In one aspect,the cancer is colorectal cancer.

In other aspects, the invention includes a step of detecting theexpression level of a CCPM mRNA. In other aspects, the inventionincludes a step of detecting the expression level of a CCPM polypeptide.In yet a further aspect, the invention includes a step of detecting thelevel of a CCPM peptide. In yet another aspect, the invention includesdetecting the expression level of more than one CCPM family member insaid sample. In a further aspect the CCPM is a gene associated with animmune response. In a further aspect the CCPM is selected from themarkers set forth in Tables 3, 4, 8A, 8B, or 9. In a still furtheraspect, the CCPM is included in a signature selected from the signaturesset forth in Tables 3, 4, 8A, 8B, or 9.

In a further aspect the invention comprises detecting the expressionlevel of; WDR44, RBMS1, SACM1L, SOAT1, PBK, G3BP2, ZBTB20, ZNF410,COMMD2, PSMC1, COX10, GTF3C5, HMMR, UBE2L3, GNAS, PPP2R2A, RNASE2, SCOCPSMD9, EIF3S7, ATP2B4, and ABCC9. In a further aspect the inventioncomprises detecting the expression level of; CXCL10, FAS, CXCL9, TLK1,CXCL11, PBK, PSAT1, MAD2L1, CA2, GZMB, SLC4A4, DLG7, TNFRSF11A, KITLG,INDO, GBP1, CXCL13, CLCA4, and PCP4.

In still further aspects, the invention includes a method of determininga treatment regime for a cancer comprising: (a) providing a sample ofthe cancer; (b) detecting the expression level of a CCPM family memberin said sample; (c) determining the prognosis of the cancer based on theexpression level of a CCPM family member; and (d) determining thetreatment regime according to the prognosis.

In still further aspects, the invention includes a device for detectinga CCPM, comprising: a substrate having a CCPM capture reagent thereon;and a detector associated with said substrate, said detector capable ofdetecting a CCPM associated with said capture reagent. Additionalaspects include kits for detecting cancer, comprising: a substrate; aCCPM capture reagent; and instructions for use. Yet further aspects ofthe invention include method for detecting a CCPM using qPCR,comprising: a forward primer specific for said CCPM; a reverse primerspecific for said CCPM; PCR reagents; a reaction vial; and instructionsfor use.

Additional aspects of this invention comprise a kit for detecting thepresence of a CCPM polypeptide or peptide, comprising: a substratehaving a capture agent for said CCPM polypeptide or peptide; an antibodyspecific for said CCPM polypeptide or peptide; a reagent capable oflabeling bound antibody for said CCPM polypeptide or peptide; andinstructions for use.

In yet further aspects, this invention includes a method for determiningthe prognosis of colorectal cancer, comprising the steps of: providing atumour sample from a patient suspected of having colorectal cancer;measuring the presence of a CCPM polypeptide using an ELISA method. Inspecific aspects of this invention the CCPM of the invention is selectedfrom the markers set forth in Tables 1, 2, 5, or 9. In still furtheraspects, the CCPM is included in a prognostic signature selected fromthe signatures set forth in Tables 3, 4, 8A, 8B, or 10.

EXAMPLES

The examples described herein are for purposes of illustratingembodiments of the invention. Other embodiments, methods, and types ofanalyses are within the scope of persons of ordinary skill in themolecular diagnostic arts and need not be described in detail hereon.Other embodiments within the scope of the art are considered to be partof this invention.

Example 1 Patients and Methods

Two cohorts of patients were included in this study, one set from NewZealand (NZ) and the second from Germany (DE). The NZ patients were partof a prospective cohort study that included all disease stages, whereasthe DE samples were selected from a tumour bank. Clinical information isshown in Table 6, while FIG. 1 summarises the experimental design.

Example 2 Tumour Samples

Primary colorectal tumor samples from 149 NZ patients were obtained frompatients undergoing surgery at Dunedin Hospital and Auckland Hospitalbetween 1995-2000. Tumor samples were snap frozen in liquid nitrogen.All surgical specimens were reviewed by a single pathologist (H-S Y) andwere estimated to contain an average of 85% tumor cells. Among the 149CRC patients, 12 had metastatic disease at presentation, 35 developedrecurrent disease, and 102 were disease-free after a minimum of 5-yearfollow up.

Primary colorectal tumor samples from DE patients were obtained frompatients undergoing surgery at the Surgical Department of the TechnicalUniversity of Munich between 1995-2001. A group of 55 colorectalcarcinoma samples was selected from banked tumours which had beenobtained fresh from surgery, snap frozen in liquid nitrogen. The sampleswere obtained from 11 patients with stage I cancer and 44 patients withstage II cancer. Twenty nine patients were recurrence-free and 26patients had experienced disease recurrence after a minimum of 5-yearfollow up.

Tumor content ranged between 70 and 100% with an average of 87%.

TABLE 6 Clinical characteristics of New Zealand and German colorectaltumours Relapse free Relapse New Zealand data Number of patients 102  47Age 68.5 (SD: 15.1) 69.8 (SD: 8.7)  Gender male 48 (47%) 22 (47%) female54 (53%) 25 (53%) Tumor localization right colon 41 (40%) 18 (38%) leftcolon 12 (12%) 4 (9%) sigmoid 31 (30%) 17 (36%) rectum 18 (18%)  8 (17%)Tumor stage Stage I 16  0 Stage II 61 13 Stage III 25 22 Stage IV  0 12¹ Median follow up   72 (range: 60-80)   15 (range: 0-59)period/median recurrence free period (months) German data Number ofpatients 29 26 Age 64.3 (SD: 12.8) 61.8 (SD: 10.7) Gender male 17 (59%)16 (62%) female 12 (41%) 10 (38%) Tumor localization right colon  8(28%)  4 (15%) left colon  7 (24%)  5 (19%) sigmoid  6 (21%)  7 (27%)rectum  8 (28%) 10 (38%) Tumor stage Stage I  5  6 Stage II 24 20 Medianfollow up 83.1 (range: 64-99) 27.4 (range: 3-60) period/medianrecurrence free period (months) ¹Persisting disease

Example 3 RNA Extraction and Target Labeling

NZ tumours: Tumours were homogenized and RNA was extracted usingTri-Reagent (Progenz, Auckland, New Zealand). The RNA was then furtherpurified using RNeasy mini column (Qiagen, Victoria, Australia). Tenmicrograms of RNA was labelled with Cy5 dUTP using the indirectamino-allyl cDNA labelling protocol.

A reference RNA from 12 different cell lines was labelled with Cy3 dUTP.The fluorescently labelled cDNA were purified using a QiaQuick PCRpurification kit (Qiagen, Victoria, Australia) according to themanufacturer's protocol.

DE tumours: Tumours were homogenized and RNA was isolated using RNeasyMini Kit (Qiagen, Hilden, Germany). cRNA preparation was performed asdescribed previously (9), purified on RNeasy Columns (Qiagen, Hilden,Germany), and eluted in 55 μl of water. Fifteen micrograms of cRNA wasfragmented for 35 minutes at 95° C. and double stranded cDNA wassynthesized with a oligo-dT-T7 primer (Eurogentec, Köln, Germany) andtranscribed using the Promega RiboMax T7-kit (Promega, Madison, Wis.)and Biotin-NTP labelling mix (Loxo, Dossenheim, Germany).

Example 4 Microarray Experiments

NZ tumours: Hybridisation of the labelled target cDNA was performedusing MWG Human 30K Array oligonucleotides printed on epoxy coatedslides. Slides were blocked with 1% BSA and the hybridisation was donein pre-hybridisation buffer at 42° C. for at least 12 hours followed bya high stringency wash. Slides were scanned with a GenePix MicroarrayScanner and data was analyzed using GenePix Pro 4.1 MicroarrayAcquisition and Analysis Software (Axon, Calif.).

DE tumours: cRNA was mixed with B2-control oligonucleotide (Affymetrix,Santa Clara, Calif.), eukaryotic hybridization controls (Affymetrix,Santa Clara, Calif.), herring sperm (Promega, Madison, Wis.), buffer andBSA to a final volume of 300 μl and hybridized to one microarray chip(Affymetrix, Santa Clara, Calif.) for 16 hours at 45° C. Washing stepsand incubation with streptavidin (Roche, Mannheim, Germany),biotinylated goat-anti streptavidin antibody (Serva, Heidelberg,Germany), goat-IgG (Sigma, Taufkirchen, Germany), andstreptavidin-phycoerythrin (Molecular Probes, Leiden, Netherlands) wasperformed in an Affymetrix Fluidics Station according to themanufacturer's protocol. The arrays were then scanned with aHP-argon-ion laser confocal microscope and the digitized image data wereprocessed using the Affymetrix® Microarray Suite 5.0 Software.

Example 5 Data Pre-Processing

NZ data: Data pre-processing and normalization was performed in the Rcomputing environment (10). A log₂ transformation was applied to theforeground intensities from each channel of each array. Data from eachspot was used on a per array basis to perform print-tip lossnormalization via the limma package (11) from the Bioconductor suite ofanalysis tools (12). Scale normalization (13) was then used tostandardize the distribution of log intensity ratios across arrays.Post-normalization cluster analysis revealed the presence of agene-specific print-run effect present in the data. Analysis of variance(ANOVA) normalization was used to estimate and remove print run effectsfrom the data for each gene. Replicate array data was available for 46of the 149 samples. Cluster analysis of the entire data set indicatedthat the duplicate arrays clustered well with each other suggestinginternal consistency of the array platform. Genes with low intensity,large differences between replicates (mean log₂ difference betweenduplicates higher than 0.5), and unknown proteins were removed from thedata set. After the initial normalization procedure, a subset of 10,318genes was chosen for further analysis.

DE data: All Affymetrix U133A GeneChips passed quality control toeliminate scans with abnormal characteristics, that is, abnormal low orhigh dynamic range, high perfect match saturation, high pixel noise,grid misalignment problems, and low mean signal to noise ratio.Background correction and normalization were performed in the Rcomputing environment (10, 40). Background corrected and normalizedexpression measures from probe level data (cel-files) were obtainedusing the robust multi-array average function (14) implemented in theBioconductor package affy.

Example 6 Prognostic Signatures and Cross Validation

Data analysis was performed using the BRB Array-Tools package (hypertexttransfer protocol://linus.nci.nih.gov/BRB-ArrayTools.html). Geneselection was performed using a random variance model t-test. In the DEdata, 318 genes were found to be differentially expressed when using asignificance threshold of 0.001. As most of the differentially expressedgenes exhibited relatively small changes in expression, a conditionrequiring the mean log₂ fold change between the two classes to be higherthan 1.1 was added to the gene selection process for the DE data.Gene-based prognostic signatures were produced using leave one out crossvalidation (LOOCV) in each of the NZ and DE data sets. To avoid theproblem of over-fitting, both the gene selection and signatureconstruction were performed during each LOOCV iteration. After LOOCV,the prediction rate was estimated by the fraction of samples correctlypredicted. In order to find a gene set that could make the bestprediction for unknown samples, different t-test thresholds using arandom variance model were investigated in conjunction with sixclassification methods: compound covariate classifier (CCP), diagonallinear discriminant analysis (DLD), 3-nearest neighbours (3-NN),1-nearest neighbours (1-NN), nearest centroid (NC), and support vectormachines (SVM).

To establish the validity of the NZ and DE prognosis signatures,reciprocal validation was performed, with the NZ signature validatedusing the DE data set, and vice versa. To test the NZ genes, probesrelating to the 22 genes from the NZ signature were identified in the DEdata, and LOOCV was used to assess the performance of a signature forthe DE samples, based only on these probes. Similarly, probes relatingto the 19 genes in the DE signature were identified in the NZ data andLOOCV was used to assess the performance of a signature for the NZsamples. In both cases a significance threshold of 0.999 was used toensure that all genes were used in each LOOCV iteration. Differencesbetween the platforms (in particular, log-ratio data versuslog-intensity data) meant that direct application of a prediction ruleacross data sets was not feasible. The consequence of this is that onlythe gene sets, and not the prediction rules used, can be generalized tonew samples. The significance of the LOOCV prediction results wascalculated by permuting the class labels of the samples and finding theproportion of times that the permuted data resulted in a higher LOOCVprediction rate than that obtained for the unpermuted data. Allpermutation analysis involved 2000 permutations, with small P-valuesindicating that prediction results were unlikely to be due to chance.

Example 7 Survival Analysis

Kaplan-Meier survival analysis for censored data was performed using thesurvival package within the R computing environment. Survival wasdefined to be “disease free survival” post surgery. For each analysis,survival curves were constructed, and the log-rank test (15) was used toassess the presence of significant differences between the curves forthe two groups in question. Censoring was taken into account for boththe NZ and DE data sets. For the disease-free survival data, rightcensoring prior to five years could only occur for non-recurrentpatients as a result of either death, or the last clinical follow-upoccurring at less than five years. Odds ratios and confidence intervalswere produced using the epitools package for R.

Example 8 Identification of Markers Co-Expressed with Chemokine Ligands

Genes in the DE data which had a Pearson correlation coefficient greaterthan 0.75 with at least one of the four chemokines appearing in thepredictor in the non-relapse group were selected for ontology analysis.Ontology was performed using DAVID (hypertext transferprotocol://appsl.niaid.nih.gov/david/).

Example 9 Results and Analysis

To identify robust prognostic signatures to predict disease relapse forCRC, two independent sets of samples from NZ and DE were used togenerate array expression data sets from separate series of primarytumours with clinical follow-up of five or more years. Afternormalization, each data set was analyzed using the same statisticalmethods to generate a prognostic signature, which was then validated onthe alternate series of patients. As such, the DE prognostic signaturewas validated on the NZ data set and the NZ prognostic signature wasvalidated on the DE data set.

Example 10 Exhaustive Identification of Differentially Expressed Markers

DE Data Set: The BRB Array Tools class comparison procedure was used todetect probes exhibiting statistically significant differences inaverage intensity between relapse and non-relapse samples. The RVM(random variance model) was again used to produce p-values for eachprobe in the data set. In this second round, a total of 325 probes werefound to be significantly differentially expressed between the twosample classes using an arbitrary significance threshold of 0.05. Notethis selection of genes did not apply any fold-change threshold, andused a significance cut off of 0.05, rather than the threshold of 0.001that was used in Example 6. The purpose of this less stringent threshold(p=0.05 instead of p=0.001) was to put forward a larger number of genesfor construction of the second round of signatures (see example 17)These probes represent 270 unique genes (Table 1 and Table 2).

Explicitly, the test for significance (random variance model) comprisesthe following: generating a test statistic for each gene which wasidentical to that of a standard two sample t-test (45) except that theestimate of the pooled variance was obtained by representing thevariance structure across all genes as an F-distribution, and then usingthe parameters, a and b, of this distribution (obtained via maximizationof the empirical likelihood function) to form the following estimate ofthe pooled variance (see next page),

$s^{2} = \frac{{\left( {n - 2} \right)s_{pooled}^{2}} + {2\; b^{- 1}}}{\left( {n - 2} \right) + {2\; a}}$

where S² is the new estimate of the pooled variance, S² _(pooled) is thestandard estimate of pooled variance (45), n is the number of samples,and a and b are the parameters of the F-distribution (46). Based on thet-statistic formed, a t-distribution with n−2+2a degrees of freedom wasused to obtain a p-value for each gene. To adjust for multiplehypothesis testing, the False Discovery Rate controlling procedure ofBenjamini and Hochberg (7) was used to produce adjusted p-values foreach gene. A gene was considered to have undergone significantdifferential expression if its adjusted p-value was less than 0.05.

Example 11 Identification of Correlated Markers

In order to identify additional genes that can be used as prognosticpredictors, correlation analysis was carried out using the R statisticalcomputing software package. This analysis revealed 167 probes that had aPearson correlation coefficient (40, 44, 45) of at least 0.8. Of theseprobes, 51 were already present in the set of 325 significantlydifferentially expressed probes, while the remaining 116 were reportedas non-significant (using a 0.05 threshold for the FDR, or“false-discovery rate” (47) controlling procedure, the RVM, or randovariance model). These 116 probes represent 111 distinct genes (Table2).

Example 12 Construction of Prognostic Signatures

The NZ data set was generated using oligonucleotide printed microarrays.Six different signatures were constructed, with a support vector machine(SVM) using a gene selection threshold of 0.0008 yielding the highestLOOCV prediction rate, and producing a 22-gene signature (77% predictionrate, 53% sensitivity, 88% specificity; p=0.002, Tables 7, 8A, and 8B).For Tables 8A and 8B, the gene descriptions are shown in Tables 3 and 4,respectively.

TABLE 7 Construction of prognostic signatures Data set Prediction rateSensitivity Specificity P value* Odd ratio 22 gene NZ signature testedon German data NZ data 0.77 0.53 0.88 0.002 8.4 (training; SVM) (0.66,0.86)^(§) (0.33, 0.73) (0.77, 0.95) (3.5, 21.4) NZ data minus 4 genes0.72 0.38 0.87 0.011 not found in German data were removed from NZ dataset (training; SVM) German data (test; SVM) 0.71 0.62 0.79 0.002 5.9(0.51, 0.86) (0.32, 0.86) (0.52, 0.95) (1.6, 24.5) 19 gene Germansignature tested on NZ data German data 0.84 0.85 0.83 <0.0001 24.1(training; 3-NN) (0.65, 0.95) (5.3, 144.7) German data minus 5 0.67 0.650.66 0.046 genes not found in NZ data were removed from German data set(training; 3-NN) NZ data (test; 3-NN) 0.67 0.42 0.78 0.045 2.6 (0.55,0.78) (0.22, 0.64) (0.65, 0.89) (1.2, 6.0) SVM: support vector machinesignature; 3-NN: 3 nearest neighbour signature. ^(§)95% confidenceinterval *P values were calculated from 2,000 permutation of classlabels

TABLE 8A NZ prognostic signature New Zealand 22-gene prognosticsignature Gene GenBank Genes not found in German p-value Symbol Acc. No.data at time of analysis 2.30E−05 WDR44 NM_019045 * 3.30E−05 RBMS1NM_016836 4.60E−05 SACM1L NM_014016 6.80E−05 SOAT1 NM_003101 7.90E−05PBK NM_018492 0.00014 G3BP2 NM_012297 0.000163 ZBTB20 NM_015642 0.000214ZNF410 NM_021188 * 0.00022 COMMD2 NM_016094 * 0.000293 PSMC1 NM_0028020.000321 COX10 NM_001303 0.000334 GTF3C5 NM_012087 0.000367 HMMRNM_012485 0.000405 UBE2L3 NM_003347 0.000417 GNAS NM_000516 0.000467PPP2R2A NM_002717 0.000493 RNASE2 NM_002934 0.000532 SCOC NM_032547 *0.000578 PSMD9 NM_002813 0.000593 EIF3S7 NM_003753 0.000649 ATP2B4NM_001001396 NM_001684 0.000737 ABCC9 NM_020298

TABLE 8B DE prognostic signature German 19-gene prognostic signatureGene GenBank Genes not found in NZ p-value Symbol Acc. No. data at timeof analysis 3.00E−06 CXCL10 NM_001565 4.00E−06 FAS NM_000043 NM_152871NM_152872 NM_152873 NM_152874 NM_152875 NM_152876 NM_152877 8.00E−06CXCL9 NM_002416 * 1.20E−05 TLK1 NM_012290 1.30E−05 CXCL11 NM_0054092.10E−05 PBK NM_018492 4.20E−05 PSAT1 NM_021154 7.60E−05 MAD2L1NM_002358 9.80E−05 CA2 NM_000067 0.000128 GZMB NM_004131 * 0.000177SLC4A4 NM_003759 0.000215 DLG7 NM_014750 * 0.000376 TNFRSF11A NM_0038390.00038 KITLG NM_000899 0.000579 INDO NM_002164 0.000634 GBP1 NM_0020530.000919 CXCL13 NM_006419 * 0.000942 CLCA4 NM_012128 * 0.001636 PCP4NM_006198

The NZ signature had an odds ratio for disease recurrence in the NZpatients of 8.4 (95% CI 3.5-21.4).

The DE data set was generated using Affymetrix arrays resulting in a19-gene (22-probe) and 3-nearest neighbour (3-NN) signature (selectionthreshold 0.002, log₂ fold change>1.1, 84% classification rate, 85%sensitivity, 83% specificity, p<0.0001, Tables 3, 4, 7). The DEsignature had an odds ratio for recurrence in the DE patients of 24.1(95% CI 5.3-144.7). Using Kaplan-Meier analysis, disease-free survivalin NZ and DE patients was significantly different for those predicted torecur or not recur (NZ signature, p<0.0001, FIG. 2A; DE signature,p<0.0001, FIG. 2B).

Example 13 External Validation of the NZ and DE Prognostic Signatures

To validate the NZ signature, the 22 genes were used to construct a SVMsignature in the DE data set by LOOCV. A prediction rate of 71% wasachieved, which was highly significant (p=0.002; Table 7). The oddsratio for recurrence in DE patients, using the NZ signature, was 5.9(95% CI 1.6-24.5). We surmise that the reduction in prediction rate,from 77% in NZ patients to 71% in DE patients (Table 7), was due to fourgenes from the NZ signature not being present in the DE data.Disease-free survival for DE patients predicted to relapse, according tothe NZ signature, was significantly lower than disease-free survival forpatients predicted not to relapse (p=0.0049, FIG. 2C).

The DE signature was next validated by using the 19 genes to construct a3-NN signature in the NZ data set by LOOCV. The prediction rate of 67%was again significant (p=0.046; Table 7), confirming the validity of theDE signature. The odds ratio for recurrence in NZ patients, using the DEsignature, was 2.6 (95% CI 1.2-6.0). We consider that the reduction ofthe prediction rate was due to five genes from DE signature not beingpresent in the NZ data set. This was confirmed when removal of thesefive genes from the DE data set resulted in a reduction of the LOOCVprediction rate from 84% to 67% (Table 7). Disease-free survival for NZpatients predicted to relapse, according to the DE signature, wassignificantly lower than disease-free survival for patients predictednot to relapse (p=0.029; FIG. 2D).

Example 14 Comparison of NZ and DE Prognostic Signatures with CurrentStaging System

Significant differences in disease-free survival between patientspredicted to relapse or not relapse were also observed within the sameclinico-pathological stage (FIG. 3). When patient predictions werestratified according to disease stage, the NZ signature was able toidentify patients who were more likely to recur in both Stage II(p=0.0013, FIG. 3A), and Stage III subgroups (p=0.0295, FIG. 3A). Thiswas mirrored to a lesser extent when the DE signature was applied to theNZ data set, where the difference was only observed for Stage IIIpatients (p=0.0491, FIG. 3B). Again, the decreased predictive accuracyof the DE signature was likely due to the absence of five genes from theNZ data that decreased the LOOCV prediction rate.

Example 15 Genes in Signatures are Related to CRC Disease Progression

A number of genes in the NZ signature (Table 3) including G3BP2 (16),RBMS1 (17), HMMR (18), UBE2L3 (19), GNAS (20), RNASE2 (21) and ABCC9(22) have all been reported to be involved in cancer progression, whileRBMS1 (23), EIF3S7 (24) and GTF3C5 (25) are involved in transcription ortranslation. PBK is a protein kinase, which is involved in the processof mitosis (26), and the only gene common to the NZ and DE signatures.Eleven of 19 genes in the DE signature (Table 4) are involved in theimmune response including 4 chemokine ligands (CXCL9, CXCL10, CXCL11,CXCL13; (27)), PBK (28), INDO (29), GBP1 (30), GZMB (31), KITLG (32),and two receptors of the tumor necrosis factor family (TNFRSF11A, FAS;33)).

Eighty six genes were found to be moderately correlated (Pearsoncorrelation coefficient >0.75) with at least one of the four chemokineligands in the DE data. Ontology analysis found that 39 of these 65genes were in the category of immune response (p<10⁻²⁶). This resultsuggests a key role for the host immune response in determining CRCrecurrence.

Example 16 Discussion of NZ and DE Prognostic Signatures

It has been shown that the two different prognostic signatures can beused to improve the current prognosis of colorectal cancer.

For the DE signature, it was surprising and unexpected that the stageI/II samples could be used to predict stage III outcome. It was alsosurprising that many genes associated with recurrent disease are relatedto the immune response. The immune response has an important role in theprogression of different cancers and T-lymphocyte infiltration in CRCpatients is an indicator of good prognosis (36-38). All of the elevenimmune response (Table 5) genes were down-regulated in recurrentpatients which would be unexpected based on known biological mechanisms.

To further confirm these results, 4 chemokine genes were chosen forfurther analysis. Chemokine ligands not only reflect the activity of theimmune system and mediate leukocyte recruitment but also are involved inchemotaxis, cell adhesion and motility, and angiogenesis (36). Toinvestigate the role of the immune response genes, 86 genes co-expressedwith the chemokine ligands were identified. Almost half of these geneshad a Gene Ontology classification within the “immune response” categorysuggesting that the primary function of these genes in the recurrenceprocess is the modulation of the immune response. Furthermore, CD4+ andCD8+T cell antigens (CD8A, CD3, PRF1, TRAa, TRBa) or functionallyrelated antigens, for example, major histocompatibility molecules,interferon gamma induced proteins, and IL2RB, were found in theco-expressed gene list. The activation of tumor specific CD4+T cells andCD8+T cells has been shown to result in tumour rejection in a mousecolorectal cancer model (37). Collectively, these findings suggest thatthe lymphocytes form part of a tumor-specific host response involved inminimising the spread of cells from the primary tumour.

Example 17 Selection of Additional Prognostic Signatures

The performance of the two prognostic signatures described above wasexcellent in terms of cross-validation between the two data sets.Further studies were carried out, using a purely statistical approach,to develop a range of signatures, in addition to the aforementioned,that would also predict prognosis for other data sets. One of theadditional goals of these studies was to ensure that the method used tonormalize the microarray data (robust multi-array average) was notexerting undue influence on the choice of genes.

FIG. 4 shows the classification rates obtained from signatures ofvarying lengths. The classification rate is the proportion of correctrelapse predictions (expressed as a percentage of total predictions),i.e., the proportion of samples correctly classified. The classificationrates were determined using 11-fold cross validation. For this crossvalidation, a randomly selected stratified sample (i.e. same ratio ofrecurrent to non-recurrent tumours as the full data set) was removed asa validation set prior to gene selection of the genes, and modelconstruction (using the training set of the remaining 50 samples).Cross-validation was then repeated a further ten times so that all 55samples appeared in one validation set each. This 11-foldcross-validation process was repeated as 10 replicates, and the resultsplotted in FIG. 4 and FIG. 5. The classification rates shown werecorrected using bootstrap bias correction (43), to give the expectedclassification rates for the signatures to be applied to another dataset. From this analysis, it was ascertained that shorter signaturesproduced the best classification rate. In addition, analysis of thegenes that most frequently appeared in classifiers show that thediscriminatory power was mostly due to the effectiveness of two genes:FAS and ME2. This is illustrated most clearly by FIG. 5 shows theeffectiveness of the signatures, once the two genes FAS and ME2 wereremoved from the data set. For more detail see the legend to FIG. 5.

The effect of normalization on feature selection was thoroughlyinvestigated by generating gene lists from 1000 stratified sub-samplesof the original set of tumours, each time removing 5 samples (i.e. 1/11of the total number of samples) from the data set. (This is effectivelythe same as performing 11-fold cross-validation). A tally was made ofthe number of times each gene appeared in the “top-n” gene lists (i.e.,top 10, top 20, top 100, and top 325). This value was termed the “topcount”. Top counts were generated using three different normalizationmethods (40) (FIG. 6), and three different filtering statistics (FIG.7). There was substantial correlation in the top count betweennormalization schemes and filtering statistics (41, 42) used. Thus,while normalization and feature selection methods were important, manygenes appeared in the gene lists independently of the method used topre-process the data. This indicates that the choice of normalizationmethod had only a minimal effect on which genes were selected for use insignature construction. The top count, summed across all normalizationmethods and statistics, was found to be a robust measure of a gene'sdifferential expression between recurrent and non-recurrent tumours.

Genes from the gene lists (see Table 1 and Table 2), were used togenerate signatures by random sampling. The generation of samples wasweighted, such that genes with higher “top count” were more likely to beselected. A range of signatures was generated, using between 2 and 55Affymetrix probes. Signatures were selected if they exhibited >80%median classification rate, using three methods of classifiers:k-nearest neighbours, with k=1; k-nearest neighbours, with k=3; andsupport vector machines, with a linear kernel function, and usingleave-one-out cross-validation.

On average, longer prognostic signatures were preferred over shortersignatures in terms of ability to predict prognosis for new data sets(FIG. 4 and FIG. 5). The genes FAS and ME2 were also important(discussed, above). These two facts were used, along with the fact thatshort signatures that do not contain either FAS or ME2 perform lesseffectively, to select candidate signatures as shown in Table 9, below.Signatures were selected (from the pool of randomly generatedsignatures) if they exhibited >80% median classification rate (usingthree methods of classifiers: k-nearest neighbours, with k=1; k-nearestneighbours, with k=3; and support vector machines, with a linear kernelfunction), using leave-one-out cross-validation.

In addition, because, on average, longer signatures (>10genes/signature) tended to perform better, we selected signatures with20 or more genes/signatures from a pool of signatures with 30 or moreprobes/signature. It is expected that these signatures (Table 10) willperform with a classification rate of around 70% when applied to otherdata sets, on the basis of the results shown in FIGS. 4 and 5. It wasfound that all of the signatures generated in this way contained bothME2, and all but one contained FAS, which may be due to the importanceof these genes in providing prediction of prognosis. It was noted thatthe high classification rate obtained using this approach on thein-house data set did not necessarily mean that these signatures thatwould be expected to perform better than those set forth in Example 12,on other data sets. Rather, the purpose was to produce a range ofsignatures expected to apply to other data sets as least as well as theprevious signatures. The markers comprising the prognostic signaturesare set forth in Table 9.

TABLE 9 Additional Prognostic signatures (note SVM = support vectormachine, 3NN = 3 nearest neighbours, 1NN = 1 nearest neighbour, Sens =sensitivity, Spec = specificity, for prediction of recurrence) SignatureSVM 3NN 1NN Number Signature Genes (as gene symbols) Sens Spec Sens SpecSens Spec 1 WARS, STAT1, EIF4E, PRDX3, PSME2, 81% 86% 73% 90% 77% 83%GMFB, DLGAP4, TYMS, CTSS, MAD2L1, CXCL10, C1QBP, NDUFA9, SLC25A11,HNRPD, ME2, CXCL11, RBM25, CAMSAP1L1, hCAP-D3, BRRN1, ATP5A1, FAS,FLJ13220, PBK, BRIP1 2 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 77% 86% 85%79% 81% 86% GMFB, DLGAP4, TYMS, LMAN1, CDC40, CXCL10, NDUFA9, SLC25A11,CA2, ME2, IFT20, TLK1, CXCL11, RBM25, AK2, FAS, FLJ13220, PBK, PSAT1,STAT1 3 WARS, SFRS2, PRDX3, GMFB, DLGAP4, 85% 86% 92% 76% 85% 79% TYMS,LMAN1, CDC40, CXCL10, NDUFA9, KPNB1, SLC25A11, CA2, ME2, FUT4, CXCL11,GZMB, RBM25, ATP5A1, CDC42BPA, FAS, RBBP4, HNRPD, BRIP1, STAT1 4 WARS,PRDX3, MTHFD2, PSME2, TES, 81% 79% 77% 69% 77% 79% DCK, CDC40, CXCL10,PLK4, NDUFA9, SLC25A11, WHSC1, ME2, CXCL11, SLC4A4, RBM25, ATP5A1,CDC42BPA, FAS, BAZ1A, AGPAT5, FLJ13220, HNRPD, KLHL24, STAT1 5 HNRPD,WARS, MTHFD2, GMFB, 88% 83% 88% 83% 88% 76% DLGAP4, TYMS, CXCL9, IRF8,GTSE1, RABIF, CXCL10, FAS, TRIM25, KITLG, C1QBP, SLC25A11, C17orf25,CA2, ME2, SLC4A4, CXCL11, RBM25, KLHL24, STAT1 6 HNRPD, WARS, STAT1,PRDX3, 73% 83% 81% 79% 65% 66% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS,CXCL9, PLK4, KITLG, NDUFA9, ME2, CXCL11, SLC4A4, AK2, FAS, AGPAT5,FLJ13220, PBK, ETNK1 7 WARS, EIF4E, PRDX3, TK1, GMFB, 88% 90% 88% 90%85% 86% DLGAP4, TYMS, LMAN1, ARF6, FAS, CHEK1, NDUFA9, SLC25A11, WHSC1,CA2, ME2, CXCL11, IFT20, SLC4A4, RBM25, hCAP-D3, CDC42BPA, FLJ13220,HNRPD, STAT1 8 WARS, EPAS1, EIF4E, PRDX3, PSME2, 77% 86% 85% 79% 77% 79%TK1, GMFB, DLGAP4, TYMS, DCK, CDC40, CXCL9, CXCL10, C1QBP, NDUFA9,SLC25A11, WHSC1, ME2, TLK1, RBM25, BRRN1, FAS, BRIP1, TRMT5, KLHL24,STAT1 9 HNRPD, WARS, PRDX3, MTHFD2, 69% 79% 85% 83% 77% 79% PSME2, GMFB,DLGAP4, TYMS, TES, CDC40, IRF8, CXCL10, FAS, CHEK1, KITLG, WHSC1, CA2,ME2, TLK1, RBM25, AK2, NUP210, ATP5A1, BRIP1 STAT1 10 HNRPD, EPAS1,EIF4E, PRDX3, DLGAP4, 85% 79% 85% 79% 77% 72% TES, CTSS, DCK, CXCL9,CXCL10, FAS, PLK4, HNRPA3P1, SLC25A11, C1QBP, C17orf25, CA2, ME2, RBM25,AK2, SEC10L1, FLJ13220, TRMT5, STAT1 11 HNRPD, WARS, EIF4E, PRDX3,PSME2, 85% 83% 92% 76% 85% 76% GBP1, GMFB, DLGAP4, TYMS, TES, RABIF,CXCL10, C1QBP, NDUFA9, SLC25A11, C17orf25, ME2, FUT4, CXCL11, RBM25,AK2, hCAP-D3, FAS, AGPAT5, SEC10L1, PBK, STAT1 12 HNRPD, MTHFD2, PSME2,GMFB, 88% 79% 92% 69% 92% 83% DLGAP4, TYMS, DCK, IRF8, NDUFA9, SLC25A11,C17orf25, CA2, ME2, CXCL11, GZMB, RBM25, NUP210, SOCS6, DDAH2, FAS,RBBP4, MARCH5, SEC10L1, KLHL24, STAT1 13 WARS, EPAS1, STAT1, MTHFD2,MCM6, 88% 90% 88% 76% 77% 69% GBP1, GMFB, DLGAP4, TYMS, ARF6, CXCL10,FAS, KITLG, NDUFA9, CA2, ME2, GZMB, CXCL11, RBM25, RBBP4, PBK, PSAT1,HNRPD 14 WARS, EPAS1, EIF4E, PRDX3, PSME2, 85% 83% 92% 76% 92% 79% GBP1,TK1, GMFB, TYMS, CXCL9, FAS, CHEK1, SLC25A11, NDUFA9, WHSC1, CA2, ME2,FUT4, CXCL11, RBM25, CAMSAP1L1, SFRS2, DDAH2, AGPAT5, HNRPD, BRIP1,ETNK1 15 SFRS2, EIF4E, PRDX3, MTHFD2, MCM6, 81% 83% 81% 83% 77% 79% TK1,GMFB, TYMS, TES, CTSS, ARF6, CXCL9, RABIF, CXCL10, FAS, KITLG, SLC25A11,ME2, IFT20, SLC4A4, CXCL11, RBM25, PSAT1, HNRPD, TRMT5, STAT1 16 WARS,SFRS2, EPAS1, EIF4E, PRDX3, 92% 93% 81% 83% 81% 83% TYMS, LMAN1, CDC40,CXCL9, CXCL10, PLK4, CHEK1, SLC25A11, C1QBP, NDUFA9, ME2, IFT20, SLC4A4,CXCL11, RBM25, DDAH2, FAS, HNRPD, BRIP1, STAT1 17 WARS, EIF4E, GMFB,DLGAP4, TYMS, 92% 90% 85% 79% 81% 76% CTSS, MAD2L1, SLC4A4, CXCL9, IRF8,CXCL10, FAS, TRIM25, KPNB1, SLC25A11, HNRPD, ME2, CXCL11, RBM25, AK2,hCAP-D3, DDAH2, SEC10L1, ETNK1, STAT1 18 HNRPD, WARS, SFRS2, MTHFD2,PSME2, 81% 79% 85% 90% 81% 93% TK1, GMFB, DLGAP4, ARF6, CXCL10, TRIM25,NDUFA9, SLC25A11, WHSC1, ME2, CXCL11, TLK1, RBM25, CAMSAP1L1, hCAP-D3,CDC42BPA, FAS, AGPAT5, STAT1 19 HNRPD, WARS, SFRS2, STAT1, EIF4E, 96%86% 73% 76% 73% 66% PSME2, TYMS, USP4, DCK, ARF6, CXCL9, RABIF, CXCL10,C1QBP, SLC25A11, ME2, IFT20, SLC4A4, CXCL11, RBM25, AK2, SOCS6, FAS,ETNK1 20 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 77% 79% 73% 83% 81% 86%PSME2, GMFB, TES, ARF6, CXCL10, FAS, KITLG, C1QBP, SLC25A11, C17orf25,ME2, FUT4, CXCL11, RBM25, ATP5A1, FLJ13220, PSAT1, HNRPD, STAT1 21 WARS,PSME2, GMFB, DLGAP4, USP4, 77% 72% 85% 83% 85% 79% ARF6, CDC40, CXCL9,IRF8, RABIF, CXCL10, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1,C17orf25, ME2, TLK1, SLC4A4, RBM25, hCAP-D3, SOCS6, FAS, AGPAT5,SEC10L1, KLHL24, STAT1 22 WARS, MTHFD2, PSME2, GBP1, TK1, 77% 79% 77%76% 81% 72% GMFB, DLGAP4, CXCL9, CXCL10, CHEK1, TRIM25, SLC25A11,C17orf25, HNRPD, ME2, SLC4A4, RBM25, AK2, BRRN1, FAS, DKFZp762E1312,SEC10L1, PBK, TRMT5, STAT1 23 HNRPD, WARS, STAT1, EIF4E, PRDX3, 85% 83%92% 90% 85% 76% DLGAP4, TYMS, ARF6, CXCL9, CXCL10, FAS, HNRPA3P1, C1QBP,NDUFA9, SLC25A11, WHSC1, ME2, CXCL11, RBM25, MARCH5, SEC10L1, BRIP1 24WARS, PRDX3, PSME2, GMFB, DLGAP4, 85% 83% 77% 69% 81% 69% CTSS, LMAN1,CXCL9, CXCL10, HNRPA3P1, SLC25A11, NDUFA9, C17orf25, ME2, FUT4, SLC4A4,RBM25, AK2, FAS, MARCH5, PBK, HNRPD, KLHL24, ETNK1, STAT1 25 WARS,PRDX3, MTHFD2, PSME2, GMFB, 81% 83% 77% 83% 81% 72% DLGAP4, TYMS, USP4,CDC40, CXCL9, CXCL10, TRIM25, NDUFA9, CA2, ME2, TLK1, CXCL11, SLC4A4,RBM25, AK2, ATP5A1, SOCS6, DDAH2, FAS, MARCH5, PBK, STAT1 26 WARS,EIF4E, MTHFD2, PSME2, GMFB, 81% 83% 92% 86% 81% 79% DLGAP4, TYMS, ARF6,CXCL10, PLK4, CHEK1, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2,CXCL11, RBM25, CAMSAP1L1, FAS, SEC10L1, FLJ13220, STAT1 27 WARS, SFRS2,EIF4E, MTHFD2, PSME2, 85% 90% 85% 86% 81% 79% TK1, TYMS, LMAN1, CDC40,CXCL10, C1QBP, NDUFA9, KPNB1, CA2, ME2, GZMB, TLK1, SLC4A4, RBM25,ATP5A1, FAS, AGPAT5, SEC10L1, FLJ13220, HNRPD, STAT1 28 HNRPD, WARS,EPAS1, MTHFD2, 88% 86% 81% 86% 81% 76% PSME2, TK1, TYMS, CXCL9, CXCL10,FAS, TRIM25, KITLG, C1QBP, NDUFA9, CA2, ME2, CXCL11, RBM25, AK2, BRRN1,FLJ10534, SEC10L1, PBK, ETNK1, STAT1 29 EIF4E, PRDX3, PSME2, DLGAP4,CTSS, 88% 86% 88% 76% 77% 69% CXCL9, GTSE1, CXCL10, FAS, PLK4, KITLG,SLC25A11, CA2, ME2, GZMB, CXCL11, RBM25, AK2, AGPAT5, MARCH5, FLJ13220,PBK, HNRPD, STAT1 30 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 77% 79% 81% 79%65% 69% PSME2, DLGAP4, TYMS, CTSS, CDC40, CXCL9, CXCL10, FAS, PLK4,NDUFA9, ME2, CXCL11, RBM25, AK2, BRRN1, RBBP4, HNRPD, KLHL24, ETNK1,STAT1 31 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 85% 83% 92% 76% 92% 72%GMFB, DLGAP4, TYMS, ARF6, CDC40, CXCL9, TRIM25, SLC25A11, CA2, ME2,IFT20, CXCL11, RBM25, BRRN1, CDC42BPA, FAS, AGPAT5, FLJ10534, HNRPD,TRMT5, STAT1 32 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 85% 79% 77% 83% 77%72% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, CTSS, DCK, CXCL9, CXCL10, FAS,KITLG, NDUFA9, ME2, CXCL11, RBM25, ATP5A1, PBK, ETNK1, STAT1 33 WARS,SFRS2, MTHFD2, PSME2, MCM6, 73% 79% 92% 90% 88% 79% GMFB, DLGAP4, TYMS,LMAN1, CDC40, SLC4A4, CXCL10, FAS, CHEK1, SLC25A11, C1QBP, WHSC1,C17orf25, CA2, ME2, RBM25, SOCS6, AGPAT5, HNRPD, STAT1 34 HNRPD, WARS,MTHFD2, PSME2, GMFB, 85% 86% 92% 90% 81% 86% DLGAP4, RABIF, CXCL10,TRIM25, KITLG, C1QBP, KPNB1, SLC25A11, WHSC1, ME2, RBM25, CAMSAP1L1,BRRN1, CDC42BPA, FAS, AGPAT5, SEC10L1, ETNK1, STAT1 35 HNRPD, WARS,SFRS2, SFPQ, MTHFD2, 81% 83% 85% 79% 73% 79% DLGAP4, TYMS, USP4, LMAN1,ARF6, CDC40, C1QBP, C17orf25, CA2, ME2, CXCL11, SLC4A4, RBM25, AK2,ATP5A1, FAS, SEC10L1, FLJ13220, ETNK1, STAT1 36 WARS, SFRS2, EIF4E,PRDX3, MTHFD2, 85% 83% 85% 90% 88% 90% PSME2, GMFB, DLGAP4, LMAN1, ARF6,MAD2L1, GTSE1, CXCL10, FAS, KITLG, SLC25A11, WHSC1, ME2, FUT4, IFT20,RBM25, AGPAT5, HNRPD, STAT1 37 WARS, SFRS2, EIF4E, MTHFD2, TK1, 73% 79%92% 83% 85% 86% GMFB, DLGAP4, TYMS, LMAN1, CXCL10, CHEK1, HNRPA3P1,C1QBP, NDUFA9, SLC25A11, ME2, CXCL11, RBM25, BRRN1, CDC42BPA, FAS,SEC10L1, PSAT1, HNRPD, KLHL24, STAT1 38 WARS, EPAS1, EIF4E, PRDX3,MTHFD2, 85% 86% 77% 90% 85% 90% GMFB, DLGAP4, TYMS, CTSS, LMAN1, DCK,CDC40, RABIF, CXCL10, HNRPA3P1, C1QBP, C17orf25, ME2, CXCL11, TLK1,RBM25, FAS, FLJ13220, HNRPD, KLHL24, STAT1 39 WARS, SFRS2, EIF4E, PRDX3,MTHFD2, 88% 83% 88% 79% 85% 72% GMFB, DLGAP4, TYMS, CTSS, SLC4A4,CXCL10, SLC25A11, C17orf25, HNRPD, ME2, CXCL11, RBM25, AK2, CDC42BPA,FAS, AGPAT5, SEC10L1, TRMT5, STAT1 40 SFRS2, EIF4E, PRDX3, PSME2, GMFB,85% 93% 88% 83% 81% 69% DLGAP4, TYMS, CXCL9, IRF8, RABIF, CXCL10, FAS,TRIM25, SLC25A11, NDUFA9, ME2, CXCL11, RBM25, AGPAT5, FLJ13220, HNRPD,BRIP1, ETNK1, STAT1 41 HNRPD, WARS, EIF4E, PRDX3, TK1, 85% 83% 96% 79%92% 72% DLGAP4, TYMS, CDC40, CXCL9, GTSE1, CXCL10, FAS, KITLG, SLC25A11,NDUFA9, ME2, IFT20, SLC4A4, RBM25, NUP210, BAZ1A, SEC10L1, TRMT5,KLHL24, STAT1 42 WARS, SFRS2, EIF4E, PRDX3, PSME2, 81% 79% 85% 83% 92%69% DLGAP4, TYMS, CTSS, CXCL9, IRF8, CXCL10, FAS, C1QBP, NDUFA9, KPNB1,SLC25A11, ME2, SLC4A4, RBM25, SOCS6, MARCH5, SEC10L1, HNRPD, BRIP1,STAT1 43 WARS, EPAS1, PRDX3, PSME2, TK1, 77% 83% 88% 62% 92% 72% GMFB,DLGAP4, TYMS, CTSS, CDC40, CXCL9, CXCL10, SLC25A11, C1QBP, WHSC1, ME2,GZMB, RBM25, SFRS2, FAS, AGPAT5, SEC10L1, PSAT1, KLHL24, ETNK1, STAT1 44WARS, PSME2, GMFB, DLGAP4, TYMS, 85% 86% 96% 79% 81% 83% CDC40, CXCL10,FAS, PLK4, C1QBP, NDUFA9, SLC25A11, CA2, ME2, CXCL11, IFT20, TLK1,RBM25, NUP210, BAZ1A, MARCH5, PSAT1, TRMT5, STAT1 45 WARS, PRDX3,MTHFD2, PSME2, TYMS, 88% 90% 85% 79% 88% 66% CXCL10, FAS, CHEK1, TRIM25,C1QBP, NDUFA9, C17orf25, CA2, ME2, CXCL11, IFT20, RBBP4, RBM25, AK2,CDC42BPA, AGPAT5, DKFZp762E1312, HNRPD, STAT1 46 WARS, SFRS2, EIF4E,SFPQ, PRDX3, 81% 79% 81% 79% 77% 72% MTHFD2, PSME2, DLGAP4, TYMS, USP4,CDC40, CXCL10, FAS, HNRPA3P1, KITLG, NDUFA9, KPNB1, SLC25A11, WHSC1,CA2, ME2, CXCL11, SLC4A4, RBM25, hCAP-D3, BRRN1, CDC42BPA, AGPAT5,MARCH5, SEC10L1, FLJ13220, BRIP1, ETNK1, STAT1 47 HNRPD, WARS, EIF4E,PRDX3, MTHFD2, 81% 83% 88% 86% 88% 69% PSME2, GMFB, DLGAP4, TYMS, CTSS,MAD2L1, CDC40, CXCL9, CXCL10, KITLG, NDUFA9, SLC25A11, WHSC1, C17orf25,CA2, ME2, SLC4A4, CXCL11, RBM25, AK2, ATP5A1, CDC42BPA, FAS, BAZ1A,AGPAT5, SEC10L1, BRIP1, TRMT5, STAT1 48 WARS, EIF4E, SFPQ, PRDX3,MTHFD2, 77% 83% 81% 79% 73% 69% PSME2, GMFB, DLGAP4, TYMS, USP4, ARF6,CXCL9, CXCL10, FAS, HNRPA3P1, C1QBP, NDUFA9, KPNB1, SLC25A11, ME2,CXCL11, IFT20, TLK1, RBM25, RBBP4, AGPAT5, MARCH5, SEC10L1, PBK, PSAT1,HNRPD, BRIP1, STAT1 49 HNRPD, WARS, SFRS2, EIF4E, SFPQ, 77% 83% 77% 79%81% 83% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES, DCK, ARF6,CXCL9, CXCL10, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, ME2, CXCL11, IFT20,TLK1, RBM25, AK2, hCAP-D3, ATP5A1, FAS, MARCH5, KLHL24, STAT1 50 WARS,STAT1, EIF4E, SFPQ, PRDX3, 81% 79% 85% 83% 77% 66% MTHFD2, TK1, GMFB,DLGAP4, TYMS, CTSS, CXCL9, IRF8, CXCL10, PLK4, TRIM25, C1QBP, NDUFA9,SLC25A11, C17orf25, ME2, SLC4A4, AK2, CAMSAP1L1, FAS, BAZ1A, MARCH5,FLJ13220, PBK, BRIP1, KLHL24, ETNK1 51 HNRPD, WARS, EIF4E, PRDX3,MTHFD2, 77% 79% 85% 79% 85% 72% GMFB, DLGAP4, TYMS, TES, ARF6, CXCL9,CXCL10, TRIM25, SLC25A11, NDUFA9, WHSC1, CA2, ME2, SLC4A4, CXCL11,RBM25, hCAP-D3, ATP5A1, FAS, RBBP4, SEC10L1, FLJ13220, PBK, BRIP1,KLHL24, ETNK1, STAT1 52 WARS, EPAS1, STAT1, EIF4E, MTHFD2, 77% 83% 81%86% 69% 76% PSME2, GBP1, GMFB, DLGAP4, TYMS, DCK, CDC40, CXCL9, CXCL10,FAS, HNRPA3P1, SLC25A11, C1QBP, ME2, FUT4, CXCL11, SLC4A4, RBM25, AK2,CAMSAP1L1, SFRS2, DDAH2, RBBP4, AGPAT5, FLJ10534, DKFZp762E1312, PSAT1,HNRPD 53 HNRPD, WARS, SFRS2, SFPQ, PRDX3, 88% 83% 92% 79% 92% 72%MTHFD2, PSME2, GMFB, DLGAP4, TYMS, LMAN1, CDC40, CXCL9, GTSE1, FAS,HNRPA3P1, SLC25A11, NDUFA9, KPNB1, CA2, ME2, CXCL11, SLC4A4, RBM25,BRRN1, CDC42BPA, RBBP4, BAZ1A, SEC10L1, BRIP1, KLHL24, STAT1 54 HNRPD,WARS, EPAS1, PAICS, EIF4E, 77% 79% 85% 83% 85% 79% PRDX3, MTHFD2, PSME2,MCM6, GMFB, DLGAP4, TYMS, USP4, LMAN1, MAD2L1, CDC40, SLC4A4, CXCL9,CXCL10, FAS, KITLG, C1QBP, SLC25A11, ME2, CXCL11, RBM25, AK2, CDC42BPA,SFRS2, SEC10L1, STAT1 55 WARS, EPAS1, STAT1, EIF4E, SFPQ, 88% 90% 88%76% 88% 79% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES, CXCL9, IRF8,CXCL10, FAS, NDUFA9, C17orf25, CA2, HNRPD, ME2, CXCL11, IFT20, RBM25,CDC42BPA, FLJ10534, SEC10L1, PBK, BRIP1, TRMT5 56 SFRS2, PAICS, EIF4E,PRDX3, MTHFD2, 85% 79% 85% 79% 81% 86% PSME2, GMFB, DLGAP4, TYMS, TES,LMAN1, SLC4A4, CXCL9, CXCL10, FAS, PLK4, TRIM25, SLC25A11, NDUFA9,WHSC1, C17orf25, ME2, FUT4, CXCL11, IFT20, RBM25, ATP5A1, CDC42BPA,FLJ10534, SEC10L1, HNRPD, KLHL24, STAT1 57 SFRS2, PAICS, EIF4E, SFPQ,PRDX3, 81% 86% 85% 79% 85% 83% MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS,CTSS, LMAN1, SLC4A4, CXCL9, IRF8, CXCL10, TRIM25, NDUFA9, C17orf25, CA2,HNRPD, ME2, CXCL11, IFT20, RBM25, AK2, ATP5A1, FAS, PBK, BRIP1, TRMT5,ETNK1, STAT1 58 HNRPD, WARS, SFRS2, STAT1, EIF4E, 81% 76% 92% 79% 88%72% MTHFD2, PSME2, DLGAP4, TYMS, DCK, CDC40, CXCL9, IRF8, CXCL10, PLK4,SLC25A11, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2, NUP210, SOCS6,CDC42BPA, FAS, AGPAT5, SEC10L1, FLJ13220, BRIP1, KLHL24, ETNK1 59 WARS,SFRS2, MTHFD2, PSME2, GMFB, 81% 79% 88% 86% 85% 83% DLGAP4, TYMS, CDC40,CXCL9, GTSE1, CXCL10, FAS, PLK4, TRIM25, SLC25A11, C1QBP, NDUFA9, KPNB1,WHSC1, C17orf25, CA2, ME2, CXCL11, TLK1, RBM25, BRRN1, AGPAT5, MARCH5,HNRPD, BRIP1, TRMT5, KLHL24, STAT1 60 HNRPD, WARS, SFRS2, EIF4E, SFPQ,92% 79% 77% 86% 69% 76% MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS,LMAN1, CDC40, CXCL9, CXCL10, FAS, CHEK1, C1QBP, NDUFA9, SLC25A11, WHSC1,ME2, TLK1, CXCL11, RBM25, CDC42BPA, AGPAT5, FLJ10534, FLJ13220, PSAT1,STAT1 61 WARS, EPAS1, EIF4E, MTHFD2, PSME2, 77% 83% 85% 72% 85% 69%GMFB, DLGAP4, TYMS, TES, LMAN1, ARF6, CDC40, CXCL9, CXCL10, FAS, PLK4,TRIM25, C1QBP, C17orf25, CA2, ME2, CXCL11, SLC4A4, RBM25, AK2, ATP5A1,CDC42BPA, AGPAT5, FLJ10534, DKFZp762E1312, SEC10L1, PBK, PSAT1, STAT1 62HNRPD, WARS, STAT1, EIF4E, SFPQ, 85% 76% 88% 83% 77% 69% PSME2, TK1,GMFB, DLGAP4, TYMS, TES, CXCL9, GTSE1, CXCL10, FAS, CHEK1, C1QBP,NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11, SLC4A4, RBM25,CDC42BPA, DDAH2, AGPAT5, FLJ13220, PBK, TRMT5, KLHL24, ETNK1 63 WARS,EIF4E, PRDX3, PSME2, TK1, 81% 83% 65% 83% 73% 72% GMFB, DLGAP4, TYMS,USP4, DCK, MAD2L1, CXCL10, TRIM25, C1QBP, NDUFA9, SLC25A11, C17orf25,HNRPD, ME2, CXCL11, IFT20, RBBP4, TLK1, SLC4A4, RBM25, AK2, CAMSAP1L1,SOCS6, FAS, FLJ10534, FLJ13220, PBK, BRIP1, ETNK1, STAT1 64 WARS, SFRS2,EIF4E, SFPQ, PRDX3, 69% 79% 73% 83% 85% 83% MTHFD2, PSME2, TK1, GMFB,DLGAP4, TYMS, LMAN1, CXCL9, IRF8, RABIF, CXCL10, CHEK1, NDUFA9, ME2,FUT4, CXCL11, SLC4A4, RBM25, AK2, CAMSAP1L1, FAS, RBBP4, MARCH5,SEC10L1, PBK, PSAT1, HNRPD, TRMT5, KLHL24, STAT1 65 HNRPD, WARS, SFPQ,MTHFD2, PSME2, 85% 72% 88% 79% 77% 72% GMFB, DLGAP4, CTSS, LMAN1, ARF6,CDC40, SLC4A4, CXCL9, CXCL10, FAS, CHEK1, KITLG, C1QBP, NDUFA9,SLC25A11, WHSC1, ME2, FUT4, GZMB, IFT20, RBM25, CAMSAP1L1, BAZ1A,AGPAT5, SEC10L1, PBK, KLHL24, ETNK1, STAT1 66 HNRPD, WARS, SFRS2, STAT1,PRDX3, 81% 76% 96% 69% 81% 66% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, LMAN1,ARF6, IRF8, RABIF, CXCL10, PLK4, HNRPA3P1, SLC25A11, C1QBP, CA2, ME2,GZMB, CXCL11, RBM25, NUP210, ATP5A1, DDAH2, FAS, PSAT1, BRIP1, TRMT5,KLHL24, ETNK1 67 WARS, EPAS1, STAT1, EIF4E, SFPQ, 77% 83% 92% 79% 77%69% PSME2, GMFB, DLGAP4, TYMS, CTSS, DCK, SLC4A4, CXCL9, CXCL10, C1QBP,NDUFA9, SLC25A11, C17orf25, CA2, ME2, FUT4, CXCL11, RBM25, AK2, NUP210,CAMSAP1L1, FAS, AGPAT5, FLJ13220, PBK, HNRPD, ETNK1 68 HNRPD, WARS,SFRS2, EIF4E, PRDX3, 77% 76% 88% 79% 92% 79% MTHFD2, GMFB, TYMS, TES,CDC40, SLC4A4, CXCL9, CXCL10, PLK4, HNRPA3P1, SLC25A11, C1QBP, NDUFA9,C17orf25, CA2, ME2, CXCL11, RBM25, NUP210, hCAP-D3, SOCS6, FAS, SEC10L1,PBK, TRMT5, KLHL24, STAT1 69 HNRPD, WARS, EIF4E, PRDX3, MTHFD2, 81% 83%92% 72% 77% 79% PSME2, GBP1, GMFB, DLGAP4, TYMS, TES, CTSS, CXCL9,CXCL10, FAS, CHEK1, C1QBP, NDUFA9, SLC25A11, CA2, ME2, GZMB, TLK1,CXCL11, RBM25, BRRN1, MARCH5, FLJ13220, PBK, TRMT5, KLHL24, ETNK1, STAT170 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 79% 85% 83% 85% 79% MTHFD2,PSME2, TK1, GMFB, DLGAP4, USP4, TES, LMAN1, CDC40, CXCL9, IRF8, CXCL10,KITLG, NDUFA9, SLC25A11, WHSC1, CA2, ME2, CXCL11, RBM25, AK2, CAMSAP1L1,FAS, SEC10L1, PBK, BRIP1, TRMT5, STAT1 71 HNRPD, WARS, PAICS, EIF4E,MTHFD2, 85% 86% 88% 76% 81% 72% PSME2, GMFB, DLGAP4, TYMS, USP4, TES,CXCL9, CXCL10, FAS, TRIM25, C1QBP, SLC25A11, C17orf25, CA2, ME2, CXCL11,IFT20, RBBP4, RBM25, AK2, hCAP-D3, ATP5A1, BAZ1A, PBK, BRIP1, KLHL24,ETNK1, STAT1 72 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 81% 83% 85% 86% 88%83% PSME2, MCM6, GMFB, TYMS, USP4, CXCL9, GTSE1, RABIF, CXCL10, FAS,PLK4, CHEK1, SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, ME2, FUT4, IFT20,RBBP4, SLC4A4, CXCL11, RBM25, hCAP-D3, FLJ10534, MARCH5, HNRPD, TRMT5,STAT1 73 HNRPD WARS, EIF4E, PRDX3, PSME2, 73% 79% 81% 79% 77% 76% TK1,DLGAP4, TYMS, CTSS, LMAN1, ARF6, CXCL9, CXCL10, CHEK1, TRIM25, NDUFA9,KPNB1, SLC25A11, WHSC1, ME2, SLC4A4, RBM25, AK2, SFRS2, DDAH2, FAS,FLJ10534, MARCH5, FLJ13220, BRIP1, TRMT5, KLHL24, ETNK1, STAT1 74 WARS,SFRS2, EIF4E, MTHFD2, PSME2, 92% 86% 81% 83% 88% 76% DLGAP4, TYMS, USP4,TES, MAD2L1, SLC4A4, CXCL9, CXCL10, CHEK1, HNRPA3P1, TRIM25, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, ME2, IFT20, TLK1, CXCL11, RBM25, BRRN1,ATP5A1, FAS, AGPAT5, PBK, HNRPD, ETNK1, STAT1 75 HNRPD, WARS, MTHFD2,PSME2, GMFB, 85% 86% 88% 79% 85% 76% DLGAP4, TYMS, TES, LMAN1, CDC40,GTSE1, CXCL10, FAS, KITLG, C1QBP, NDUFA9, SLC25A11, CA2, ME2, CXCL11,GZMB, IFT20, TLK1, SLC4A4, RBM25, hCAP-D3, BRRN1, DDAH2, MARCH5,FLJ13220, PBK, BRIP1, KLHL24, STAT1 76 HNRPD, WARS, EIF4E, MTHFD2,PSME2, 85% 83% 88% 86% 85% 83% MCM6, GMFB, DLGAP4, TYMS, TES, CTSS,LMAN1, CDC40, SLC4A4, IRF8, GTSE1, CXCL10, CHEK1, HNRPA3P1, TRIM25,NDUFA9, WHSC1, CA2, ME2, CXCL11, RBM25, NUP210, ATP5A1, CDC42BPA, SFRS2,FAS, MARCH5, SEC10L1, BRIP1, STAT1 77 HNRPD, WARS, EPAS1, EIF4E, PRDX3,96% 83% 92% 83% 88% 79% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, ARF6, SLC4A4,CXCL10, PLK4, CHEK1, HNRPA3P1, KPNB1, SLC25A11, WHSC1, C17orf25, CA2,ME2, CXCL11, IFT20, RBBP4, TLK1, RBM25, CDC42BPA, SFRS2, FAS, AGPAT5,FLJ10534, SEC10L1, TRMT5, STAT1 78 WARS, SFRS2, STAT1, PAICS, EIF4E, 81%83% 92% 76% 85% 76% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, LMAN1,MAD2L1, SLC4A4, CXCL9, CXCL10, SLC25A11, C17orf25, CA2, ME2, FUT4, GZMB,CXCL11, RBM25, CAMSAP1L1, BRRN1, CDC42BPA, FAS, FLJ10534, SEC10L1, PBK,TRMT5, KLHL24 79 HNRPD, WARS, SFRS2, PRDX3, 81% 72% 88% 79% 88% 69%MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, TES, CXCL9, CXCL10, FAS, KITLG,C1QBP, NDUFA9, C17orf25, CA2, ME2, RBM25, SOCS6, CDC42BPA, BAZ1A,AGPAT5, DKFZp762E1312, SEC10L1, FLJ13220, PSAT1, BRIP1, TRMT5, KLHL24,STAT1 80 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 85% 86% 81% 69% 69% 69%PSME2, TK1, DLGAP4, TYMS, TES, CTSS, ARF6, CXCL9, CXCL10, FAS, HNRPA3P1,TRIM25, SLC25A11, C1QBP, NDUFA9, HNRPD, ME2, CXCL11, RBBP4, RBM25, AK2,AGPAT5, FLJ10534, DKFZp762E1312, SEC10L1, PBK, KLHL24, STAT1 81 EIF4E,SFPQ, MTHFD2, PSME2, GMFB, 81% 79% 85% 76% 81% 66% DLGAP4, TYMS, TES,CTSS, CXCL9, CXCL10, FAS, PLK4, NDUFA9, WHSC1, C17orf25, CA2, HNRPD,ME2, IFT20, RBM25, NUP210, CDC42BPA, DDAH2, BAZ1A, AGPAT5, FLJ10534,DKFZp762E1312, SEC10L1, FLJ13220, PBK, BRIP1, TRMT5, STAT1 82 WARS,SFRS2, STAT1, EIF4E, PRDX3, 81% 90% 85% 76% 85% 72% MTHFD2, PSME2, GMFB,DLGAP4, TYMS, TES, LMAN1, DCK, CDC40, CXCL9, CXCL10, FAS, TRIM25, C1QBP,NDUFA9, SLC25A11, CA2, ME2, CXCL11, SLC4A4, RBM25, AK2, BRRN1, AGPAT5,DKFZp762E1312, FLJ13220, PBK 83 SFRS2, STAT1, EIF4E, PRDX3, MTHFD2, 65%79% 77% 83% 77% 79% PSME2, GMFB, DLGAP4, TYMS, USP4, TES, CTSS, LMAN1,ARF6, CDC40, IRF8, CXCL10, CHEK1, C1QBP, SLC25A11, WHSC1, ME2, SLC4A4,CXCL11, RBM25, NUP210, FAS, FLJ10534, MARCH5, FLJ13220, PSAT1, HNRPD,BRIP1, TRMT5, KLHL24 84 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 85% 83% 88%76% 73% 72% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, CTSS, ARF6, MAD2L1,CXCL10, TRIM25, KITLG, NDUFA9, WHSC1, CA2, ME2, GZMB, IFT20, CXCL11,RBM25, FAS, AGPAT5, MARCH5, PSAT1, BRIP1, TRMT5, STAT1 85 HNRPD, SFRS2,STAT1, PRDX3, 88% 76% 92% 76% 81% 69% MTHFD2, PSME2, GMFB, DLGAP4, USP4,CTSS, ARF6, SLC4A4, CXCL9, RABIF, CXCL10, FAS, TRIM25, KITLG, C1QBP,SLC25A11, WHSC1, CA2, ME2, GZMB, RBBP4, CXCL11, RBM25, AGPAT5, MARCH5,SEC10L1, PBK, BRIP1, TRMT5 86 WARS, STAT1, EIF4E, MTHFD2, PSME2, 85% 76%81% 83% 81% 76% DLGAP4, TYMS, USP4, LMAN1, CDC40, CXCL9, IRF8, CXCL10,PLK4, TRIM25, C1QBP, NDUFA9, SLC25A11, CA2, ME2, CXCL11, RBM25, ATP5A1,SFRS2, FAS, AGPAT5, MARCH5, FLJ13220, PBK, HNRPD, BRIP1, TRMT5, KLHL24,ETNK1 87 HNRPD, WARS, EPAS1, STAT1, EIF4E, 73% 79% 88% 83% 69% 72%MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, SLC4A4, CXCL9, IRF8,GTSE1, RABIF, CXCL10, FAS, PLK4, HNRPA3P1, TRIM25, SLC25A11, C1QBP,NDUFA9, WHSC1, ME2, CXCL11, TLK1, RBM25, AK2, NUP210, BRRN1, ATP5A1,SFRS2, AGPAT5, FLJ10534, MARCH5, PSAT1, BRIP1, KLHL24 88 WARS, SFRS2,EPAS1, STAT1, EIF4E, 73% 83% 85% 79% 81% 72% PRDX3, MTHFD2, PSME2, TK1,GMFB, DLGAP4, TYMS, LMAN1, MAD2L1, CDC40, CXCL9, IRF8, CXCL10, FAS,CHEK1, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11,IFT20, SLC4A4, RBM25, CDC42BPA, BAZ1A, AGPAT5, MARCH5, PBK, PSAT1,HNRPD, BRIP1, TRMT5, ETNK1 89 HNRPD, WARS, SFRS2, STAT1, EIF4E, 77% 76%88% 79% 85% 66% PRDX3, MTHFD2, PSME2, GMFB, TYMS, USP4, CTSS, DCK,CDC40, SLC4A4, CXCL9, CXCL10, FAS, CHEK1, SLC25A11, C1QBP, NDUFA9,WHSC1, CA2, ME2, GZMB, RBBP4, RBM25, ATP5A1, SOCS6, AGPAT5, MARCH5,DKFZp762E1312, SEC10L1, PBK, BRIP1, TRMT5, KLHL24 90 WARS, SFRS2, EIF4E,PRDX3, MTHFD2, 77% 79% 88% 76% 88% 76% PSME2, TK1, GMFB, DLGAP4, TYMS,USP4, CTSS, SLC4A4, CXCL9, IRF8, GTSE1, CXCL10, PLK4, CHEK1, HNRPA3P1,KITLG, SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, ME2, GZMB, CXCL11, RBM25,AK2, SOCS6, DDAH2, FAS, RBBP4, FLJ10534, MARCH5, DKFZp762E1312, PBK,HNRPD, BRIP1, KLHL24, STAT1 91 HNRPD, WARS, SFRS2, EPAS1, STAT1, 69% 83%81% 79% 77% 76% EIF4E, SFPQ, PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS,USP4, TES, DCK, ARF6, MAD2L1, CDC40, SLC4A4, CXCL9, RABIF, CXCL10, FAS,SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, ME2, FUT4, CXCL11, IFT20,RBBP4, RBM25, CAMSAP1L1, SEC10L1, PBK, PSAT1, KLHL24 92 HNRPD, WARS,STAT1, EIF4E, MTHFD2, 77% 83% 92% 83% 77% 66% PSME2, TK1, GMFB, DLGAP4,TYMS, TES, CTSS, MAD2L1, SLC4A4, CXCL9, CXCL10, FAS, CHEK1, HNRPA3P1,SLC25A11, C1QBP, NDUFA9, WHSC1, CA2, ME2, GZMB, CXCL11, RBM25, AK2,CAMSAP1L1, DDAH2, BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK, BRIP1, TRMT5 93HNRPD, WARS, SFRS2, EPAS1, STAT1, 73% 83% 77% 79% 77% 76% EIF4E, MTHFD2,PSME2, GMFB, DLGAP4, TYMS, TES, CTSS, DCK, MAD2L1, CDC40, RABIF, CXCL10,FAS, PLK4, KITLG, SLC25A11, NDUFA9, WHSC1, CA2, ME2, CXCL11, IFT20,TLK1, RBM25, CDC42BPA, DDAH2, RBBP4, MARCH5, DKFZp762E1312, PBK, PSAT1,BRIP1, KLHL24, ETNK1 94 HNRPD, WARS, STAT1, PAICS, EIF4E, 88% 83% 85%76% 85% 69% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, TES,CTSS, DCK, ARF6, CDC40, CXCL9, IRF8, RABIF, CXCL10, FAS, HNRPA3P1,TRIM25, SLC25A11, NDUFA9, WHSC1, CA2, ME2, CXCL11, GZMB, IFT20, SLC4A4,SFRS2, AGPAT5, FLJ10534, MARCH5, PBK, BRIP1 95 WARS, SFRS2, STAT1,EIF4E, MTHFD2, 73% 79% 85% 83% 85% 79% PSME2, GMFB, DLGAP4, TYMS, TES,CTSS, LMAN1, DCK, MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, CXCL10, FAS,C1QBP, NDUFA9, WHSC1, CA2, ME2, CXCL11, IFT20, RBM25, hCAP-D3, ATP5A1,DDAH2, FLJ10534, MARCH5, DKFZp762E1312, SEC10L1, PBK, HNRPD, BRIP1,TRMT5, KLHL24 96 HNRPD, WARS, SFRS2, EPAS1, STAT1, 85% 86% 92% 76% 77%69% EIF4E, PRDX3, MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4,ARF6, CXCL9, CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, SLC25A11, C1QBP, WHSC1,CA2, ME2, CXCL11, GZMB, IFT20, RBM25, NUP210, SOCS6, AGPAT5, MARCH5,SEC10L1, PBK, BRIP1, ETNK1 97 HNRPD, WARS, SFRS2, EPAS1, STAT1, 92% 90%88% 76% 77% 66% EIF4E, MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, TES,DCK, CDC40, SLC4A4, CXCL9, CXCL10, FAS, TRIM25, NDUFA9, SLC25A11, WHSC1,CA2, ME2, GZMB, IFT20, TLK1, CXCL11, RBM25, AK2, hCAP-D3, BRRN1, AGPAT5,MARCH5, FLJ13220, TRMT5, KLHL24 98 HNRPD, WARS, EIF4E, SFPQ, MTHFD2, 73%76% 92% 83% 81% 83% PSME2, TK1, GMFB, DLGAP4, TYMS, DCK, CDC40, SLC4A4,CXCL9, GTSE1, CXCL10, FAS, PLK4, CHEK1, KITLG, SLC25A11, C1QBP, NDUFA9,KPNB1, WHSC1, C17orf25, CA2, ME2, CXCL11, TLK1, RBM25, NUP210, RBBP4,AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK, TRMT5, KLHL24, ETNK1, STAT1 99WARS, EPAS1, PRDX3, MTHFD2, GMFB, 85% 86% 92% 72% 77% 69% DLGAP4, TYMS,USP4, CTSS, CDC40, SLC4A4, CXCL9, IRF8, RABIF, CXCL10, FAS, HNRPA3P1,TRIM25, SLC25A11, NDUFA9, WHSC1, C17orf25, HNRPD, ME2, FUT4, CXCL11,GZMB, RBM25, AK2, ATP5A1, CDC42BPA, SFRS2, BAZ1A, AGPAT5, MARCH5,FLJ13220, BRIP1, KLHL24, ETNK1, STAT1 100 HNRPD, WARS, SFRS2, PAICS,PRDX3, 77% 79% 88% 83% 88% 76% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS,LMAN1, ARF6, MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, GTSE1, CXCL10,HNRPA3P1, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, CA2, ME2, CXCL11,RBM25, hCAP-D3, CDC42BPA, FAS, AGPAT5, FLJ10534, MARCH5, DKFZp762E1312,SEC10L1, PBK, BRIP1, TRMT5, ETNK1, STAT1 101 HNRPD, WARS, STAT1, PAICS,EIF4E, 73% 83% 88% 86% 85% 76% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4,TYMS, TES, ARF6, CXCL9, IRF8, CXCL10, FAS, PLK4, HNRPA3P1, TRIM25,C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, ME2, CXCL11, IFT20, RBBP4,TLK1, SLC4A4, RBM25, AK2, NUP210, CAMSAP1L1, DDAH2, AGPAT5, MARCH5,SEC10L1, KLHL24, ETNK1 102 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 85% 86% 81%83% 85% 79% PRDX3, MTHFD2, PSME2, DLGAP4, TYMS, USP4, CTSS, ARF6, CDC40,CXCL10, FAS, PLK4, TRIM25, KITLG, SLC25A11, C1QBP, NDUFA9, WHSC1,C17orf25, CA2, ME2, IFT20, RBBP4, TLK1, SLC4A4, CXCL11, RBM25, AK2,BAZ1A, MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, STAT1 103 WARS,SFRS2, EIF4E, SFPQ, PRDX3, 81% 86% 85% 76% 77% 76% MTHFD2, PSME2, MCM6,TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, DCK, SLC4A4, CXCL9, CXCL10, FAS,PLK4, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, HNRPD, ME2, GZMB,IFT20, TLK1, CXCL11, RBM25, RBBP4, MARCH5, PBK, PSAT1, BRIP1, TRMT5,KLHL24, ETNK1, STAT1 104 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 85% 86% 88%72% 77% 72% PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, CDC40,CXCL9, GTSE1, CXCL10, FAS, CHEK1, HNRPA3P1, SLC25A11, C1QBP, WHSC1, CA2,ME2, GZMB, IFT20, SLC4A4, CXCL11, RBM25, BAZ1A, AUPAT5, SEC10L1,FLJ13220, PBK, PSAT1, BRIP1, TRMT5, ETNK1, STAT1 105 WARS, PAICS, EIF4E,MTHFD2, PSME2, 88% 86% 81% 83% 81% 83% MCM6, GMFB, DLGAP4, TYMS, CTSS,MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, RABIF, CXCL10, FAS, CHEK1, HNRPA3P1,TRIM25, NDUFA9, SLC25A11, CA2, HNRPD, ME2, CXCL11, IFT20, RBM25, AK2,CAMSAP1L1, BRRN1, SFRS2, DDAH2, RBBP4, SEC10L1, PBK, PSAT1, BRIP1,TRMT5, KLHL24, STAT1 106 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 90% 85%83% 81% 76% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES, LMAN1,DCK, SLC4A4, CXCL9, CXCL10, PLK4, HNRPA3P1, C1QBP, NDUFA9, SLC25A11,WHSC1, C17orf25, CA2, ME2, CXCL11, GZMB, IFT20, RBBP4, TLK1, RBM25,CAMSAP1L1, FAS, MARCH5, DKFZp762E1312, SEC10L1, PBK, STAT1 107 WARS,SFRS2, EPAS1, EIF4E, PRDX3, 85% 83% 81% 86% 81% 72% MTHFD2, PSME2, TK1,GMFB, DLGAP4, TYMS, MAD2L1, CDC40, SLC4A4, CXCL9, CXCL10, FAS, KITLG,C1QBP, NDUFA9, SLC25A11, ME2, CXCL11, IFT20, TLK1, RBM25, AK2, BRRN1,ATP5A1, CDC42BPA, RBBP4, AGPAT5, MARCH5, SEC10L1, PBK, HNRPD, BRIP1,TRMT5, ETNK1, STAT1 108 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 81% 83% 85%69% 73% 79% PSME2, TK1, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, CXCL9,GTSE1, RABIF, CXCL10, FAS, PLK4, SLC25A11, NDUFA9, KPNB1, HNRPD, ME2,FUT4, CXCL11, GZMB, IFT20, RBBP4, RBM25, CAMSAP1L1, hCAP-D3, SFRS2,DDAH2, AGPAT5, MARCH5, PBK, BRIP1, TRMT5, ETNK1, STAT1 109 HNRPD, WARS,SFRS2, EPAS1, EIF4E, 77% 79% 88% 79% 77% 72% PRDX3, MTHFD2, PSME2, GMFB,DLGAP4, TYMS, TES, CTSS, DCK, CDC40, RABIF, CXCL10, FAS, CHEK1,HNRPA3P1, TRIM25, KPNB1, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11,TLK1, RBM25, ATP5A1, CDC42BPA, FLJ10534, MARCH5, DKFZp762E1312, SEC10L1,PBK, PSAT1, KLHL24, STAT1 110 HNRPD, WARS, SFRS2, STAT1, EIF4E, 73% 79%85% 83% 88% 83% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES,ARF6, MAD2L1, CDC40, CXCL9, GTSE1, CXCL10, FAS, PLK4, CHEK1, HNRPA3P1,C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, CXCL11, IFT20, TLK1, RBM25,ATP5A1, SOCS6, AGPAT5, SEC10L1, PBK, TRMT5, KLHL24 111 HNRPD, WARS,SFRS2, EPAS1, EIF4E, 81% 90% 88% 83% 77% 76% PRDX3, MTHFD2, PSME2, GBP1,TK1, GMFB, DLGAP4, TYMS, TES, CTSS, MAD2L1, CXCL9, CXCL10, FAS, PLK4,CHEK1, SLC25A11, C1QBP, WHSC1, C17orf25, CA2, ME2, CXCL11, GZMB, TLK1,SLC4A4, RBM25, AK2, hCAP-D3, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1,KLHL24, STAT1 112 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 96% 90% 81% 76% 77%76% PSME2, GMFB, DLGAP4, TYMS, USP4, TES, CTSS, MAD2L1, CXCL9, CXCL10,TRIM25, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2,CXCL11, GZMB, TLK1, RBM25, AK2, CAMSAP1L1, BRRN1, CDC42BPA, DDAH2, FAS,MARCH5, SEC10L1, PBK, PSAT1, BRIP1, KLHL24, ETNK1, STAT1 113 HNRPD,WARS, SFRS2, STAT1, EIF4E, 65% 76% 88% 76% 85% 83% PRDX3, MTHFD2, PSME2,MCM6, GBP1, GMFB, DLGAP4, TYMS, USP4, LMAN1, DCK, ARF6, CDC40, CXCL9,CXCL10, FAS, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2,ME2, FUT4, TLK1, CXCL11, SLC4A4, RBM25, AK2, ATP5A1, AGPAT5, FLJ10534,MARCH5, SEC10L1, PBK, PSAT1 114 HNRPD, WARS, SFRS2, STAT1, MTHFD2, 81%76% 81% 79% 85% 62% PSME2, MCM6, TK1, GMFB, TYMS, USP4, LMAN1, ARF6,CXCL10, FAS, PLK4, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, CA2, ME2,GZMB, RBBP4, CXCL11, RBM25, AK2, BRRN1, ATP5A1, CDC42BPA, DDAH2, BAZ1A,AGPAT5, MARCH5, SEC10L1, PBK, BRIP1 115 HNRPD, WARS, EPAS1, STAT1,EIF4E, 81% 86% 81% 76% 81% 79% SFPQ, PRDX3, MTHFD2, PSME2, TK1, GMFB,DLGAP4, TYMS, TES, LMAN1, DCK, ARF6, CXCL9, IRF8, GTSE1, CXCL10, KITLG,NDUFA9, KPNB1, C17orf25, CA2, ME2, FUT4, CXCL11, GZMB, IFT20, TLK1,SLC4A4, RBM25, AK2, BRRN1, DDAH2, FAS, FLJ13220, PBK, PSAT1, BRIP1 116WARS, SFRS2, EPAS1, PAICS, EIF4E, 81% 79% 73% 90% 73% 69% PRDX3, MTHFD2,PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, CTSS, ARF6, CDC40, CXCL9, CXCL10,FAS, HNRPA3P1, TRIM25, SLC25A11, NDUFA9, WHSC1, HNRPD, ME2, FUT4,CXCL11, SLC4A4, RBM25, CAMSAP1L1, hCAP-D3, DDAH2, MARCH5, FLJ13220, PBK,PSAT1, TRMT5, ETNK1, STAT1 117 WARS, SFRS2, EPAS1, EIF4E, SFPQ, 92% 90%88% 79% 81% 72% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, CTSS,LMAN1, ARF6, MAD2L1, CDC40, SLC4A4, CXCL9, CXCL10, FAS, PLK4, HNRPA3P1,TRIM25, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11, GZMB,IFT20, TLK1, RBM25, ATP5A1, RBBP4, AGPAT5, PSAT1, HNRPD, KLHL24, STAT1118 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 77% 90% 88% 76% 73% 79% PSME2,GBP1, DLGAP4, TYMS, DCK, ARF6, MAD2L1, CDC40, CXCL9, IRF8, GTSE1, RABIF,CXCL10, FAS, CHEK1, TRIM25, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1,C17orf25, CA2, ME2, GZMB, IFT20, TLK1, CXCL11, RBM25, AK2, SFRS2, BAZ1A,SEC10L1, FLJ13220, PBK, PSAT1, HNRPD, BRIP1, KLHL24, STAT1 119 HNRPD,WARS, SFRS2, EPAS1, EIF4E, 77% 76% 92% 83% 92% 76% SFPQ, PRDX3, MTHFD2,PSME2, GBP1, GMFB, DLGAP4, TYMS, DCK, CDC40, CXCL9, CXCL10, PLK4, CHEK1,KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, CA2, ME2, FUT4, CXCL11,RBM25, AK2, hCAP-D3, BRRN1, FAS, AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK,TRMT5, KLHL24, ETNK1, STAT1 120 WARS, SFRS2, EPAS1, EIF4E, SFPQ, 81% 86%88% 83% 85% 72% MTHFD2, PSME2, GMFB, TYMS, USP4, CTSS, LMAN1, DCK,MAD2L1, CDC40, SLC4A4, CXCL9, CXCL10, FAS, KITLG, SLC25A11, C1QBP,NDUFA9, CA2, ME2, IFT20, CXCL11, RBM25, AK2, CAMSAP1L1, hCAP-D3, ATP5A1,CDC42BPA, BAZ1A, AGPAT5, SEC10L1, PBK, HNRPD, BRIP1, KLHL24, STAT1 121HNRPD, WARS, SFRS2, EPAS1, EIF4E, 85% 90% 88% 90% 85% 76% MTHFD2, PSME2,GMFB, DLGAP4, TYMS, LMAN1, MAD2L1, CDC40, CXCL9, CXCL10, CHEK1, TRIM25,SLC25A11, WHSC1, CA2, ME2, CXCL11, IFT20, RBBP4, SLC4A4, RBM25, AK2,NUP210, hCAP-D3, DDAH2, FAS, BAZ1A, FLJ10534, FLJ13220, PBK, BRIP1,TRMT5, ETNK1, STAT1 122 HNRPD, WARS, EPAS1, STAT1, EIF4E, 69% 76% 77%86% 69% 69% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1,CDC40, CXCL9, CXCL10, FAS, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1,C17orf25, ME2, CXCL11, RBM25, hCAP-D3, BRRN1, ATP5A1, CDC42BPA,FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, TRMT5, KLHL24, ETNK1123 WARS, SFRS2, EPAS1, EIF4E, PRDX3, 73% 83% 85% 76% 81% 79% MTHFD2,PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, CDC40, CXCL9, IRF8,CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, WHSC1,C17orf25, CA2, HNRPD, ME2, SLC4A4, CXCL11, RBM25, AK2, NUP210, AGPAT5,FLJ10534, MARCH5, DKFZp762E1312, PSAT1, BRIP1, TRMT5, STAT1 124 WARS,SFRS2, EPAS1, PAICS, EIF4E, 77% 76% 92% 76% 85% 72% MTHFD2, PSME2, GMFB,DLGAP4, TYMS, CDC40, CXCL9, CXCL10, FAS, PLK4, HNRPA3P1, KITLG, C1QBP,NDUFA9, WHSC1, CA2, HNRPD, ME2, FUT4, CXCL11, GZMB, SLC4A4, RBM25, AK2,BRRN1, ATP5A1, AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK, TRMT5, KLHL24,ETNK1, STAT1 125 WARS, SFRS2, EPAS1, STAT1, EIF4E, 85% 86% 92% 86% 88%83% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, TES, CTSS, MAD2L1,CXCL9, IRF8, GTSE1, CXCL10, PLK4, CHEK1, TRIM25, NDUFA9, SLC25A11,C17orf25, CA2, HNRPD, ME2, CXCL11, IFT20, TLK1, RBM25, BRRN1, FAS,AGPAT5, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24 126 HNRPD, WARS,SFRS2, EPAS1, EIF4E, 77% 83% 88% 86% 85% 72% PRDX3, MTHFD2, PSME2, TK1,GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, ARF6, MAD2L1, CXCL9, GTSE1,CXCL10, FAS, HNRPA3P1, NDUFA9, KPNB1, SLC25A11, CA2, ME2, CXCL11, TLK1,SLC4A4, RBM25, BRRN1, AGPAT5, MARCH5, DKFZp762E1312, SEC10L1, PBK,BRIP1, KLHL24, STAT1 127 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 73% 83% 73%90% 73% 86% PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, CDC40,CXCL9, IRF8, CXCL10, PLK4, CHEK1, TRIM25, C1QBP, NDUFA9, SLC25A11,WHSC1, ME2, FUT4, CXCL11, TLK1, SLC4A4, RBM25, AK2, CAMSAP1L1, BRRN1,ATP5A1, SFRS2, FAS, SEC10L1, FLJ13220, PBK, PSAT1, TRMT5, KLHL24, STAT1128 HNRPD, EIF4E, PRDX3, MTHFD2, 69% 83% 77% 83% 85% 76% PSME2, TK1,GMFB, DLGAP4, TYMS, USP4, DCK, ARF6, MAD2L1, CDC40, CXCL9, IRF8, CXCL10,FAS, CHEK1, SLC25A11, C1QBP, NDUFA9, WHSC1, CA2, ME2, CXCL11, TLK1,SLC4A4, RBM25, AK2, BRRN1 SOCS6, DDAH2, RBBP4, FLJ10534, MARCH5,FLJ13220, PBK, BRIP1, ETNK1, STAT1 129 WARS, SFRS2, EPAS1, STAT1, EIF4E,73% 76% 92% 79% 85% 72% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS,CTSS, LMAN1, DCK, CDC40, SLC4A4, CXCL9, IRF8, CXCL10, FAS, C1QBP,NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, RBM25, NUP210, CDC42BPA,AGPAT5, SEC10L1, FLJ13220, HNRPD, BRIP1, KLHL24, ETNK1 130 HNRPD, WARS,SFRS2, EPAS1, PAICS, 85% 83% 92% 72% 88% 76% EIF4E, SFPQ, PRDX3, MTHFD2,PSME2, GMFB, DLGAP4, TYMS, CTSS, CXCL9, IRF8, RABIF, CXCL10, FAS, PLK4,CHEK1, TRIM25, KITLG, SLC25A11, C1QBP, NDUFA9, CA2, ME2, CXCL11, RBBP4,SLC4A4, RBM25, AK2, AGPAT5, FLJ10534, FLJ13220, PBK, TRMT5, KLHL24,STAT1 131 WARS, SFRS2, PRDX3, MTHFD2, PSME2, 85% 83% 92% 86% 88% 79%MCM6, GMFB, DLGAP4, TYMS, CTSS, ARF6, CDC40, CXCL9, CXCL10, FAS,HNRPA3P1, TRIM25, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1,C17orf25, CA2, HNRPD, ME2, CXCL11, TLK1, SLC4A4, RBM25, AK2, hCAP-D3,BRRN1, SOCS6, DDAH2, RBBP4, AGPAT5, PBK, BRIP1, STAT1 132 HNRPD, WARS,SFRS2, EIF4E, MTHFD2, 77% 83% 88% 76% 85% 76% PSME2, MCM6, TK1, GMFB,DLGAP4, TYMS, USP4, CTSS, LMAN1, CDC40, CXCL9, CXCL10, PLK4, HNRPA3P1,C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, CXCL11, GZMB, IFT20, SLC4A4,RBM25, AK2, ATP5A1, FAS, RBBP4, BAZ1A, MARCH5, DKFZp762E1312, SEC10L1,FLJ13220, PBK, TRMT5, KLHL24, STAT1 133 WARS, SFRS2, EPAS1, STAT1,EIF4E, 77% 83% 88% 76% 85% 79% PRDX3, MTHFD2, PSME2, MCM6, TK1, GMFB,DLGAP4, TYMS, TES, LMAN1, ARF6, CDC40, CXCL9, RABIF, CXCL10, FAS, PLK4,TRIM25, C1QBP, NDUFA9, SLC25A11, CA2, HNRPD, ME2, CXCL11, RBBP4, TLK1,RBM25, CDC42BPA, BAZ1A, AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1,BRIP1 134 WARS, SFRS2, EPAS1, PAICS, EIF4E, 81% 86% 77% 93% 81% 79%PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, CTSS, LMAN1, ARF6, MAD2L1,CDC40, IRF8, GTSE1, CXCL10, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11,WHSC1, ME2, CXCL11, RBBP4, TLK1, SLC4A4, RBM25, AK2, BRRN1, ATP5A1,CDC42BPA, DDAH2, FAS, MARCH5, SEC10L1, FLJ13220, PBK, HNRPD, BRIP1,STAT1 135 WARS, SFRS2, EPAS1, EIF4E, PRDX3, 77% 90% 88% 72% 85% 79%MTHFD2, PSME2, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, DCK, CDC40, CXCL9,IRF8, CXCL10, FAS, PLK4, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2,ME2, FUT4, CXCL11, GZMB, SLC4A4, RBM25, AK2, ATP5A1, DDAH2, FLJ10534,PBK, HNRPD, BRIP1, ETNK1, STAT1 136 WARS, SFRS2, STAT1, PRDX3, MTHFD2,81% 79% 85% 79% 81% 69% PSME2, MCM6, GMFB, DLGAP4, TYMS, TES, LMAN1,ARF6, CDC40, CXCL9, CXCL10, FAS, PLK4, HNRPA3P1, TRIM25, KITLG,SLC25A11, C1QBP, NDUFA9, KPNB1, C17orf25, CA2, ME2, IFT20, RBBP4,CXCL11, RBM25, AK2, hCAP-D3, ATP5A1, CDC42BPA, BAZ1A, AGPAT5, PBK,BRIP1, KLHL24 137 WARS, SFRS2, EPAS1, EIF4E, PRDX3, 85% 83% 81% 83% 73%72% MTHFD2, PSME2, MCM6, TK1, DLGAP4, TYMS, TES, LMAN1, ARF6, CDC40,CXCL9, CXCL10, FAS, KITLG, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, CA2,ME2, IFT20, RBBP4, TLK1, CXCL11, SLC4A4, RBM25, AK2, CDC42BPA, MARCH5,SEC10L1, FLJ13220, PBK, PSAT1, HNRPD, BRIP1, TRMT5, KLHL24, STAT1 138WARS, SFRS2, EPAS1, STAT1, PAICS, 73% 76% 85% 83% 81% 76% EIF4E, PRDX3,MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1, ARF6, CXCL9,IRF8, CXCL10, CHEK1, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2,CXCL11, SLC4A4, RBM25, AK2, BRRN1, CDC42BPA, FAS, BAZ1A, AGPAT5,FLJ10534, MARCH5, PBK, PSAT1, HNRPD, TRMT5, KLHL24 139 WARS, SFRS2,EPAS1, EIF4E, PRDX3, 85% 76% 85% 79% 77% 69% MTHFD2, PSME2, TK1, GMFB,DLGAP4, TYMS, USP4, LMAN1, ARF6, CXCL9, CXCL10, PLK4, HNRPA3P1, TRIM25,KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25, HNRPD, ME2,FUT4, CXCL11, GZMB, RBM25, AK2, hCAP-D3, BRRN1, ATP5A1, FAS, AGPAT5,SEC10L1, FLJ13220, PSAT1, TRMT5, ETNK1, STAT1 140 HNRPD, WARS, SFRS2,EPAS1, EIF4E, 81% 90% 85% 79% 81% 72% PRDX3, MTHFD2, PSME2, MCM6, GBP1,GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, SLC4A4, CXCL9, CXCL10, FAS, PLK4,CHEK1, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, GZMB,RBM25, hCAP-D3, ATP5A1, AGPAT5, FLJ10534, PBK, PSAT1, BRIP1, TRMT5,STAT1 141 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 85% 83% 88% 83% 73% 79%PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, MAD2L1, CDC40, CXCL9, IRF8,CXCL10, PLK4, HNRPA3P1, TRIM25, SLC25A11, NDUFA9, WHSC1, C17orf25, ME2,FUT4, CXCL11, IFT20, SLC4A4, RBM25, AK2, CAMSAP1L1, hCAP-D3, BRRN1, FAS,BAZ1A, AGPAT5, MARCH5, SEC10L1, FLJ13220, PSAT1, HNRPD, BRIP1, TRMT5,STAT1 142 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 77% 83% 81% 83% 85% 79%PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, CDC40, SLC4A4, CXCL9,RABIF, CXCL10, PLK4, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2,CXCL11, IFT20, RBM25, hCAP-D3, ATP5A1, SOCS6, CDC42BPA, FAS, RBBP4,BAZ1A, DKFZp762E1312, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, STAT1 143HNRPD, WARS, STAT1, EIF4E, PRDX3, 73% 72% 88% 79% 92% 76% MTHFD2, PSME2,GMFB, DLGAP4, TYMS, USP4, TES, CTSS, CDC40, CXCL9, IRF8, CXCL10, PLK4,HNRPA3P1, KITLG, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25, CA2, ME2,FUT4, CXCL11, SLC4A4, RBM25, hCAP-D3, DDAH2, FAS, RBBP4, AGPAT5,FLJ13220, PBK, BRIP1, TRMT5, KLHL24 144 WARS, SFRS2, MTHFD2, PSME2,GMFB, 73% 79% 85% 79% 69% 76% DLGAP4, TYMS, USP4, TES, CDC40, CXCL9,CXCL10, FAS, CHEK1, NDUFA9, KPNB1, WHSC1, CA2, ME2, GZMB, TLK1, RBM25,AK2, CAMSAP1L1, hCAP-D3, FLJ10534, DKFZp762E1312, FLJ13220, HNRPD, STAT1145 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 77% 79% 81% 86% 81% 83% PSME2,GMFB, DLGAP4, TYMS, LMAN1, DCK, ARF6, CDC40, CXCL9, CXCL10, PLK4,TRIM25, C1QBP, KPNB1, SLC25A11, C17orf25, ME2, CXCL11, RBM25, hCAP-D3,DDAH2, FAS, MARCH5, STAT1 146 WARS, STAT1, EIF4E, MTHFD2, PSME2, 81% 79%88% 79% 85% 69% DLGAP4, TYMS, ARF6, CXCL9, CXCL10, KITLG, C1QBP, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, SLC4A4, RBM25,hCAP-D3, SOCS6, CDC42BPA, FAS 147 HNRPD, WARS, EPAS1, EIF4E, MTHFD2, 88%83% 92% 83% 85% 83% PSME2, GMFB, DLGAP4, TYMS, ARF6, CDC40, SLC4A4,CXCL9, CXCL10, HNRPA3P1, NDUFA9, SLC25A11, CA2, ME2, TLK1, CXCL11,RBM25, ATP5A1, SFRS2, FAS, MARCH5, SEC10L1, PBK, TRMT5, STAT1 148 WARS,SFRS2, EIF4E, PRDX3, MTHFD2, 73% 83% 88% 79% 85% 72% PSME2, GMFB, TYMS,TES, LMAN1, ARF6, CXCL9, CXCL10, FAS, HNRPA3P1, C1QBP, NDUFA9, SLC25A11,WHSC1, C17orf25, CA2, ME2, CXCL11, RBM25, SEC10L1, HNRPD, KLHL24, ETNK1,STAT1 149 WARS, EIF4E, MTHFD2, PSME2, GBP1, 77% 79% 85% 76% 88% 79%GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, MAD2L1, CDC40, CXCL10, HNRPA3P1,NDUFA9, C17orf25, ME2, CXCL11, SLC4A4, RBM25, AK2, CDC42BPA, DDAH2, FAS,RBBP4, BAZ1A, AGPAT5, HNRPD, BRIP1, TRMT5, STAT1 150 WARS, SFRS2, EIF4E,PRDX3, PSME2, 85% 83% 88% 86% 85% 79% GMFB, DLGAP4, CXCL9, IRF8, CXCL10,FAS, PLK4, CHEK1, TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1,C17orf25, CA2, ME2, CXCL11, RBM25, FLJ10534, SEC10L1, BRIP1, TRMT5,STAT1 151 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 100% 97% 85% 86% 81% 72%GMFB, DLGAP4, TYMS, CTSS, DCK, SLC4A4, CXCL9, CXCL10, FAS, TRIM25,SLC25A11, C1QBP, NDUFA9, WHSC1, CA2, ME2, CXCL11, TLK1, RBM25, AK2,CDC42BPA, SEC10L1, FLJ13220, KLHL24, STAT1 152 WARS, STAT1, MTHFD2,PSME2, GMFB, 85% 90% 81% 86% 65% 86% DLGAP4, TYMS, DCK, MAD2L1, CDC40,CXCL9, IRF8, RABIF, CXCL10, KITLG, SLC25A11, NDUFA9, ME2, IFT20, TLK1,CXCL11, RBM25, AK2, FAS, AGPAT5, DKFZp762E1312, SEC10L1, PSAT1, HNRPD,TRMT5 153 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 69% 86% 85% 86% 88% 79%GMFB, DLGAP4, TYMS, DCK, CDC40, CXCL9, CXCL10, FAS, PLK4, CHEK1, C1QBP,SLC25A11, CA2, ME2, FUT4, IFT20, SLC4A4, RBM25, SFRS2, DDAH2, PBK,HNRPD, KLHL24, ETNK1, STAT1 154 HNRPD, WARS, STAT1, EIF4E, PRDX3, 88%83% 81% 83% 85% 72% PSME2, GMFB, DLGAP4, TYMS, TES, MAD2L1, CXCL9, IRF8,CXCL10, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, ME2, FUT4, IFT20, hCAP-D3,SOCS6, DDAH2, FAS, BAZ1A, PBK, KLHL24 155 SFRS2, EPAS1, EIF4E, PRDX3,PSME2, 92% 83% 88% 83% 77% 72% GMFB, TYMS, TES, LMAN1, SLC4A4, CXCL9,GTSE1, CXCL10, C1QBP, NDUFA9, SLC25A11, CA2, ME2, TLK1, RBM25, CDC42BPA,FAS, FLJ10534, MARCH5, SEC10L1, PBK, HNRPD, TRMT5, KLHL24, ETNK1, STAT1156 WARS, STAT1, EIF4E, PRDX3, MTHFD2, 81% 83% 88% 79% 92% 79% GMFB,DLGAP4, TYMS, USP4, ARF6, CDC40, CXCL9, IRF8, CXCL10, FAS, PLK4,HNRPA3P1, KITLG, C1QBP, SLC25A11, ME2, FUT4, RBM25, DDAH2, RBBP4,AGPAT5, PBK, HNRPD, TRMT5, KLHL24 157 HNRPD, WARS, SFPQ, MTHFD2, PSME2,92% 86% 85% 69% 85% 69% GMFB, DLGAP4, TYMS, USP4, SLC4A4, CXCL9, CXCL10,FAS, HNRPA3P1, KITLG, SLC25A11, NDUFA9, CA2, ME2, IFT20, CXCL11, RBM25,BAZ1A, AGPAT5, SEC10L1, PBK, BRIP1, STAT1 158 WARS, SFRS2, EIF4E,MTHFD2, PSME2, 69% 83% 92% 86% 88% 83% GMFB, DLGAP4, TYMS, ARF6, CXCL9,IRF8, CXCL10, PLK4, TRIM25, NDUFA9, WHSC1, C17orf25, CA2, ME2, CXCL11,RBBP4, TLK1, SLC4A4, RBM25, NUP210, FAS, AGPAT5, MARCH5, SEC10L1, HNRPD,STAT1 159 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 77% 76% 88% 79% 85% 66%PSME2, GBP1, GMFB, DLGAP4, TYMS, LMAN1, ARF6, CDC40, CXCL9, CXCL10, CA2,HNRPD, ME2, CXCL11, SLC4A4, RBM25, CDC42BPA, FAS, BAZ1A, AGPAT5,FLJ13220, BRIP1, KLHL24, STAT1 160 WARS, SFRS2, EPAS1, EIF4E, MTHFD2,77% 76% 77% 83% 77% 79% PSME2, TK1, GMFB, DLGAP4, LMAN1, ARF6, CDC40,CXCL9, CXCL10, PLK4, NDUFA9, C17orf25, ME2, CXCL11, SLC4A4, RBM25, FAS,BAZ1A, DKFZp762E1312, SEC10L1, PBK, PSAT1, HNRPD, STAT1 161 EIF4E,PSME2, GMFB, DLGAP4, TYMS, 92% 86% 85% 79% 88% 72% DCK, CDC40, CXCL9,CXCL10, FAS, TRIM25, KITLG, NDUFA9, SLC25A11, WHSC1, C17orf25, HNRPD,ME2, CXCL11, IFT20, SLC4A4, RBM25, AK2, AGPAT5, MARCH5, SEC10L1,FLJ13220, KLHL24, STAT1 162 HNRPD, WARS, EPAS1, EIF4E, PRDX3, 81% 79%85% 72% 85% 76% PSME2, TK1, GMFB, DLGAP4, TYMS, CTSS, CDC40, CXCL10,C1QBP, SLC25A11, C17orf25, ME2, CXCL11, SLC4A4, RBM25, CAMSAP1L1,CDC42BPA, FAS, MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, STAT1 163WARS, SFRS2, EIF4E, MTHFD2, PSME2, 69% 86% 81% 83% 81% 79% TK1, DLGAP4,TYMS, USP4, TES, DCK, CDC40, CXCL10, CHEK1, HNRPA3P1, NDUFA9, SLC25A11,WHSC1, C17orf25, CA2, ME2, RBBP4, SLC4A4, RBM25, FAS, SEC10L1, FLJ13220,BRIP1, TRMT5, STAT1 164 HNRPD, WARS, MTHFD2, TK1, GMFB, 81% 83% 92% 79%81% 83% DLGAP4, TYMS, LMAN1, CDC40, GTSE1, CXCL10, CHEK1, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, ME2, FUT4, CXCL11, RBBP4, RBM25, AK2,BRRN1, FAS, AGPAT5, MARCH5, PBK, BRIP1, STAT1 165 WARS, SFRS2, EIF4E,PRDX3, MTHFD2, 73% 83% 88% 79% 88% 76% PSME2, GMFB, DLGAP4, TYMS, USP4,DCK, CXCL9, CXCL10, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, ME2, CXCL11,SLC4A4, RBM25, CDC42BPA, FAS, AGPAT5, SEC10L1, HNRPD, BRIP1, TRMT5,STAT1 166 WARS, EIF4E, MTHFD2, PSME2, GMFB, 73% 76% 81% 83% 77% 76%TYMS, TES, CDC40, IRF8, RABIF, CXCL10, PLK4, TRIM25, SLC25A11, WHSC1,C17orf25, CA2, ME2, TLK1, CXCL11, SLC4A4, RBM25, CDC42BPA, FAS, RBBP4,SEC10L1, PBK, HNRPD, BRIP1, TRMT5, STAT1 167 WARS, SFRS2, MTHFD2, PSME2,TK1, 88% 93% 85% 76% 88% 72% DLGAP4, TYMS, DCK, CDC40, CXCL9, CXCL10,FAS, CHEK1, TRIM25, C1QBP, SLC25A11, WHSC1, CA2, ME2, CXCL11, GZMB,IFT20, SLC4A4, RBM25, hCAP-D3, DDAH2, SEC10L1, FLJ13220, PBK, KLHL24,STAT1 168 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 73% 79% 81% 86% 85% 76%MCM6, GMFB, DLGAP4, TYMS, LMAN1, DCK, CDC40, CXCL9, CXCL10, FAS, NDUFA9,WHSC1, HNRPD, ME2, SLC4A4, CXCL11, RBM25, NUP210, hCAP-D3, SEC10L1,PSAT1, KLHL24, STAT1 169 SFRS2, EIF4E, PRDX3, MTHFD2, GMFB, 73% 79% 85%86% 88% 76% DLGAP4, TYMS, USP4, LMAN1, DCK, ARF6, CDC40, CXCL9, RABIF,CXCL10, KITLG, C1QBP, SLC25A11, C17orf25, CA2, ME2, CXCL11, SLC4A4,RBM25, CAMSAP1L1, FAS, HNRPD, BRIP1, STAT1 170 WARS, SFRS2, PAICS,EIF4E, PSME2, 85% 83% 88% 83% 77% 76% GMFB, DLGAP4, TYMS, ARF6, MAD2L1,SLC4A4, CXCL9, IRF8, CXCL10, FAS, NDUFA9, WHSC1, CA2, ME2, CXCL11, TLK1,RBM25, AK2, AGPAT5, MARCH5, FLJ13220, TRMT5, STAT1 171 SFRS2, EPAS1,EIF4E, MTHFD2, GBP1, 88% 86% 85% 86% 77% 79% GMFB, CTSS, LMAN1, CDC40,CXCL9, CXCL10, FAS, CHEK1, SLC25A11, C1QBP, C17orf25, CA2, ME2, IFT20,CXCL11, RBM25, BRRN1, ATP5A1, RBBP4, HNRPD, BRIP1, STAT1 172 WARS,SFRS2, EIF4E, MTHFD2, PSME2, 81% 79% 96% 86% 88% 83% TK1, GMFB, DLGAP4,TYMS, CTSS, CDC40, SLC4A4, CXCL10, KITLG, SLC25A11, C1QBP, NDUFA9, CA2,HNRPD, ME2, FUT4, CXCL11, RBM25, ATP5A1, FAS, RBBP4, BRIP1, TRMT5, STAT1173 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 77% 79% 77% 86% 73% 86% GMFB,TYMS, TES, LMAN1, DCK, CXCL9, CXCL10, KITLG, KPNB1, SLC25A11, ME2,CXCL11, IFT20, TLK1, RBM25, CDC42BPA, FAS, BAZ1A, FLJ10534, MARCH5,SEC10L1, HNRPD, BRIP1, TRMT5, STAT1 174 HNRPD, WARS, SFRS2, EPAS1,EIF4E, 85% 79% 88% 83% 85% 86% MTHFD2, TK1, GMFB, DLGAP4, TYMS, LMAN1,CDC40, SLC4A4, CXCL9, IRF8, RABIF, CXCL10, SLC25A11, NDUFA9, CA2, ME2,CXCL11, RBBP4, RBM25, NUP210, FAS, SEC10L1, PBK, STAT1 175 HNRPD, WARS,EPAS1, PRDX3, 85% 90% 88% 83% 85% 72% MTHFD2, PSME2, DLGAP4, TYMS,CDC40, IRF8, CXCL10, FAS, SLC25A11, C1QBP, CA2, ME2, GZMB, IFT20,SLC4A4, AK2, NUP210, RBBP4, AGPAT5, MARCH5, FLJ13220, STAT1 176 HNRPD,WARS, EIF4E, MTHFD2, PSME2, 81% 79% 88% 76% 88% 79% GMFB, DLGAP4, TYMS,CXCL9, CXCL10, FAS, C1QBP, NDUFA9, SLC25A11, CA2, ME2, RBBP4, SLC4A4,CXCL11, RBM25, ATP5A1, DDAH2, BAZ1A, PBK, BRIP1, STAT1 177 HNRPD, WARS,SFRS2, EPAS1, STAT1, 96% 93% 92% 76% 88% 76% EIF4E, PRDX3, PSME2,DLGAP4, TYMS, TES, LMAN1, CDC40, CXCL10, FAS, C1QBP, NDUFA9, SLC25A11,CA2, ME2, GZMB, IFT20, CXCL11, SLC4A4, RBM25, AK2, AGPAT5,DKFZp762E1312, SEC10L1, BRIP1, KLHL24 178 WARS, EIF4E, PRDX3, MTHFD2,TK1, 85% 83% 88% 79% 88% 72% GMFB, TYMS, CDC40, CXCL9, IRF8, CXCL10,FAS, CHEK1, TRIM25, SLC25A11, NDUFA9, CA2, ME2, IFT20, RBM25, AK2,AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK, HNRPD, STAT1 179 WARS, EIF4E,PRDX3, MTHFD2, GBP1, 85% 86% 88% 76% 81% 76% GMFB, DLGAP4, TYMS, USP4,IRF8, CXCL10, FAS, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, HNRPD,ME2, GZMB, TLK1, CXCL11, RBM25, DKFZp762E1312, PSAT1, BRIP1, TRMT5,KLHL24, STAT1 180 WARS, EPAS1, STAT1, EIF4E, MTHFD2, 92% 90% 88% 79% 73%76% PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, CXCL9, IRF8, CXCL10,C1QBP, NDUFA9, SLC25A11, WHSC1, HNRPD, ME2, CXCL11, IFT20, TLK1, SLC4A4,CDC42BPA, SFRS2, FAS, PSAT1 181 WARS, EIF4E, PSME2, TK1, GMFB, 77% 79%81% 79% 85% 76% DLGAP4, TYMS, LMAN1, CDC40, CXCL9, FAS, PLK4, C1QBP,CA2, HNRPD, ME2, CXCL11, RBM25, RBBP4, SEC10L1, FLJ13220, PBK, BRIP1,TRMT5, KLHL24, ETNK1, STAT1 182 WARS, SFRS2, EIF4E, MTHFD2, GMFB, 88%83% 85% 83% 77% 86% DLGAP4, TYMS, LMAN1, CDC40, CXCL9, IRF8, GTSE1,CXCL10, HNRPA3P1, SLC25A11, NDUFA9, CA2, HNRPD, ME2, RBBP4, SLC4A4,RBM25, BRRN1, FAS, BAZ1A, BRIP1, STAT1 183 HNRPD, WARS, EPAS1, EIF4E,MTHFD2, 88% 90% 81% 86% 81% 79% TK1, GMFB, DLGAP4, LMAN1, ARF6, MAD2L1,CDC40, CXCL9, CXCL10, HNRPA3P1, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1,C17orf25, ME2, CXCL11, SLC4A4, RBM25, DDAH2, FAS, ETNK1, STAT1 184HNRPD, WARS, PAICS, MTHFD2, PSME2, 73% 83% 77% 69% 69% 69% DLGAP4, TYMS,USP4, CXCL9, CXCL10, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2, CXCL11,SLC4A4, RBM25, NUP210, ATP5A1, CDC42BPA, FAS, MARCH5, DKFZp762E1312,SEC10L1, PBK, BRIP1, STAT1 185 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 86%81% 86% 73% 83% MTHFD2, PSME2, GMFB, DLGAP4, DCK, MAD2L1, CXCL9, CXCL10,FAS, PLK4, TRIM25, KITLG, SLC25A11, WHSC1, ME2, FUT4, CXCL11, SLC4A4,RBM25, NUP210, DDAH2, RBBP4, BAZ1A, AGPAT5, FLJ10534, MARCH5,DKFZp762E1312, SEC10L1, PSAT1, BRIP1, TRMT5, STAT1 186 WARS, SFRS2,EPAS1, EIF4E, PRDX3, 85% 79% 85% 79% 73% 76% MTHFD2, PSME2, GBP1, GMFB,TYMS, LMAN1, ARF6, CDC40, CXCL9, IRF8, RABIF, CXCL10, FAS, PLK4, C1QBP,NDUFA9, SLC25A11, WHSC1, C17orf25, ME2, FUT4, CXCL11, IFT20, SLC4A4,RBM25, AK2, SOCS6, MARCH5, SEC10L1, FLJ13220, PBK, HNRPD, BRIP1, TRMT5,STAT1 187 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 77% 83% 85% 79% 81% 79%PSME2, GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, ARF6, CDC40, SLC4A4, CXCL9,RABIF, CXCL10, FAS, PLK4, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2,CXCL11, TLK1, RBM25, ATP5A1, CDC42BPA, RBBP4, AGPAT5, SEC10L1, FLJ13220,PSAT1, BRIP1, STAT1 188 HNRPD, SFRS2, EPAS1, EIF4E, PRDX3, 77% 86% 85%83% 85% 76% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1,ARF6, MAD2L1, CDC40, CXCL9, CXCL10, FAS, PLK4, NDUFA9, WHSC1, C17orf25,CA2, ME2, CXCL11, GZMB, TLK1, SLC4A4, RBM25, AK2, NUP210, hCAP-D3,DDAH2, RBBP4, PBK, BRIP1, STAT1 189 WARS, EIF4E, PRDX3, MTHFD2, GMFB,77% 79% 96% 79% 85% 72% DLGAP4, TYMS, USP4, CTSS, ARF6, CDC40, SLC4A4,CXCL9, CXCL10, FAS, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, CA2, ME2,FUT4, CXCL11, GZMB, TLK1, RBM25, NUP210, CDC42BPA, AGPAT5, MARCH5,SEC10L1, PBK, HNRPD, TRMT5, KLHL24, STAT1 190 HNRPD, WARS, SFRS2, EPAS1,EIF4E, 92% 79% 85% 83% 69% 79% MTHFD2, PSME2, GBP1, DLGAP4, TYMS, TES,LMAN1, ARF6, CDC40, CXCL9, IRF8, CXCL10, FAS, TRIM25, SLC25A11, NDUFA9,WHSC1, CA2, ME2, TLK1, CXCL11, SLC4A4, RBM25, AK2, hCAP-D3, DDAH2,FLJ10534, SEC10L1, BRIP1, STAT1 191 WARS, EPAS1, EIF4E, PRDX3, MTHFD2,77% 83% 85% 76% 85% 79% PSME2, DLGAP4, TYMS, TES, LMAN1, CDC40, CXCL9,IRF8, RABIF, CXCL10, FAS, SLC25A11, C1QBP, NDUFA9, WHSC1, CA2, ME2,CXCL11, SLC4A4, RBM25, AK2, hCAP-D3, SOCS6, CDC42BPA, FLJ10534,DKFZp762E1312, SEC10L1, FLJ13220, PBK, HNRPD, TRMT5, STAT1 192 WARS,SFRS2, STAT1, EIF4E, PRDX3, 73% 86% 85% 83% 85% 83% MTHFD2, PSME2, MCM6,TK1, GMFB, DLGAP4, TYMS, CTSS, CDC40, CXCL9, CXCL10, PLK4, KITLG,SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, ME2, CXCL11, IFT20, RBM25,hCAP-D3, ATP5A1, FAS, FLJ10534, MARCH5, SEC10L1, PBK, HNRPD, BRIP1,TRMT5 193 HNRPD, WARS, EPAS1, STAT1, EIF4E, 77% 76% 85% 83% 81% 72%PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES, MAD2L1, CXCL9,CXCL10, FAS, PLK4, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25,CA2, ME2, SLC4A4, RBM25, hCAP-D3, SOCS6, BAZ1A, FLJ10534, SEC10L1,FLJ13220, PBK, BRIP1 194 SFRS2, PAICS, EIF4E, PRDX3, MTHFD2, 77% 83% 85%83% 81% 76% PSME2, TK1, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, CDC40,CXCL9, CXCL10, FAS, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2,CXCL11, IFT20, RBBP4, SLC4A4, RBM25, AK2, hCAP-D3, BRRN1, CDC42BPA,MARCH5, FLJ13220, HNRPD, STAT1 195 WARS, SFRS2, EPAS1, EIF4E, SFPQ, 81%86% 88% 76% 85% 79% MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, DCK,ARF6, CDC40, CXCL10, FAS, CHEK1, HNRPA3P1, SLC25A11, NDUFA9, CA2, HNRPD,ME2, GZMB, RBBP4, TLK1, SLC4A4, CXCL11, RBM25, ATP5A1, AGPAT5, FLJ10534,FLJ13220, ETNK1, STAT1 196 WARS, SFRS2, STAT1, EIF4E, PRDX3, 88% 83% 88%79% 88% 72% MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, ARF6, CDC40,SLC4A4, CXCL9, GTSE1, RABIF, CXCL10, FAS, HNRPA3P1, KITLG, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, RBBP4, RBM25, AK2,CDC42BPA, MARCH5, TRMT5, KLHL24 197 WARS, SFRS2, EPAS1, STAT1, EIF4E,77% 79% 85% 79% 88% 79% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, DCK,CDC40, CXCL9, RABIF, CXCL10, FAS, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11,WHSC1, CA2, HNRPD, ME2, FUT4, CXCL11, RBM25, CDC42BPA, MARCH5,DKFZp762E1312, SEC10L1, PBK 198 WARS, SFRS2, EPAS1, EIF4E, SFPQ, 85% 90%77% 83% 77% 66% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, CDC40, RABIF,CXCL10, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, ME2,CXCL11, IFT20, RBM25, CAMSAP1L1, BRRN1, FAS, AGPAT5, PSAT1, HNRPD,TRMT5, KLHL24, ETNK1, STAT1 199 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 92%90% 96% 76% 85% 76% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, TES,LMAN1, ARF6, CDC40, CXCL9, CXCL10, FAS, KITLG, C1QBP, NDUFA9, KPNB1,SLC25A11, CA2, ME2, GZMB, RBBP4, TLK1, CXCL11, RBM25, AK2, SOCS6,AGPAT5, SEC10L1, PBK, STAT1 200 SFRS2, PAICS, EIF4E, PRDX3, PSME2, 81%86% 88% 79% 73% 72% GMFB, DLGAP4, TYMS, DCK, ARF6, MAD2L1, CDC40, CXCL9,GTSE1, RABIF, CXCL10, FAS, C1QBP, NDUFA9, SLC25A11, C17orf25, CA2, ME2,GZMB, IFT20, CXCL11, RBM25, AK2, hCAP-D3, BRRN1, AGPAT5, DKFZp762E1312,PBK, PSAT1, HNRPD, TRMT5, ETNK1, STAT1 201 HNRPD, WARS, SFRS2, STAT1,EIF4E, 88% 93% 88% 76% 85% 66% MTHFD2, PSME2, DLGAP4, TYMS, CXCL9,GTSE1, CXCL10, FAS, CHEK1, HNRPA3P1, TRIM25, KITLG, NDUFA9, SLC25A11,WHSC1, CA2, ME2, GZMB, IFT20, SLC4A4, CXCL11, RBM25, CAMSAP1L1, hCAP-D3,BRRN1, AGPAT5, MARCH5, DKFZp762E1312, SEC10L1, PBK, BRIP1 202 WARS,SFRS2, STAT1, MTHFD2, PSME2, 85% 86% 92% 76% 73% 72% MCM6, GMFB, DLGAP4,TYMS, USP4, CTSS, ARF6, CDC40, CXCL9, CXCL10, FAS, HNRPA3P1, SLC25A11,CA2, HNRPD, ME2, FUT4, RBBP4, TLK1, CXCL11, SLC4A4, RBM25, AK2,CDC42BPA, AGPAT5, DKFZp762E1312, SEC10L1, FLJ13220, PBK, KLHL24, ETNK1203 WARS, SFRS2, STAT1, MTHFD2, PSME2, 92% 86% 85% 76% 69% 69% GMFB,DLGAP4, SLC4A4, CXCL9, CXCL10, FAS, CHEK1, TRIM25, KITLG, SLC25A11,C1QBP, NDUFA9, KPNB1, WHSC1, ME2, CXCL11, IFT20, RBM25, NUP210,CAMSAP1L1, BRRN1, CDC42BPA, DDAH2, AGPAT5, DKFZp762E1312, SEC10L1,FLJ13220, PBK, HNRPD, TRMT5, KLHL24 204 WARS, SFRS2, EPAS1, EIF4E,PSME2, 85% 83% 85% 76% 81% 72% MCM6, GMFB, DLGAP4, TYMS, DCK, ARF6,SLC4A4, CXCL9, IRF8, CXCL10, FAS, KITLG, NDUFA9, SLC25A11, WHSC1, CA2,HNRPD, ME2, FUT4, GZMB, IFT20, RBBP4, CXCL11, RBM25, AK2, AGPAT5,MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, ETNK1, STAT1 205 WARS, SFRS2,EPAS1, EIF4E, MTHFD2, 96% 86% 81% 79% 85% 72% PSME2, GMFB, DLGAP4, TYMS,USP4, CTSS, LMAN1, MAD2L1, CDC40, SLC4A4, CXCL9, GTSE1, RABIF, CXCL10,FAS, PLK4, TRIM25, C1QBP, NDUFA9, SLC25A11, CA2, HNRPD, ME2, CXCL11,IFT20, RBM25, BRRN1, CDC42BPA, DDAH2, PSAT1, KLHL24, STAT1 206 WARS,PAICS, EIF4E, MTHFD2, PSME2, 81% 83% 88% 90% 77% 79% TK1, GMFB, DLGAP4,TYMS, ARF6, SLC4A4, CXCL9, CXCL10, FAS, PLK4, TRIM25, SLC25A11, C1QBP,NDUFA9, KPNB1, WHSC1, C17orf25, HNRPD, ME2, CXCL11, IFT20, TLK1, RBM25,AK2, AGPAT5, SEC10L1, FLJ13220, BRIP1, TRMT5, KLHL24, STAT1 207 WARS,SFRS2, EIF4E, PRDX3, MTHFD2, 85% 90% 96% 79% 85% 79% PSME2, GMFB,DLGAP4, TYMS, LMAN1, ARF6, CDC40, CXCL9, CXCL10, FAS, HNRPA3P1, KITLG,SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, HNRPD, ME2, FUT4,CXCL11, GZMB, IFT20, SLC4A4, RBM25, AK2, SEC10L1, PBK, BRIP1, STAT1 208HNRPD, WARS, EPAS1, STAT1, EIF4E, 77% 79% 81% 83% 73% 72% PRDX3, MTHFD2,PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, TES, CDC40, CXCL9, IRF8, GTSE1,CXCL10, FAS, C1QBP, NDUFA9, C17orf25, ME2, SLC4A4, CXCL11, RBM25,NUP210, FLJ10534, MARCH5, DKFZp762E1312, FLJ13220, PBK, BRIP1, TRMT5,ETNK1 209 WARS, EIF4E, PRDX3, MTHFD2, PSME2, 85% 86% 88% 79% 85% 76%DLGAP4, TYMS, USP4, LMAN1, MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, GTSE1,RABIF, CXCL10, FAS, TRIM25, C1QBP, NDUFA9, SLC25A11, C17orf25, CA2, ME2,CXCL11, GZMB, IFT20, TLK1, RBM25, AK2, SOCS6, RBBP4, AGPAT5, MARCH5,SEC10L1, PBK, HNRPD, STAT1 210 HNRPD, WARS, SFRS2, STAT1, EIF4E, 77% 79%85% 86% 81% 79% SFPQ, PRDX3, MTHFD2, PSME2, MCM6, DLGAP4, TYMS, ARF6,MAD2L1, CDC40, CXCL9, RABIF, CXCL10, PLK4, CHEK1, TRIM25, C1QBP, NDUFA9,WHSC1, C17orf25, CA2, ME2, CXCL11, TLK1, BRRN1, SOCS6, FAS, AGPAT5,MARCH5, FLJ13220, PBK, TRMT5, KLHL24 211 WARS, PAICS, EIF4E, PRDX3,MTHFD2, 77% 79% 85% 76% 81% 72% PSME2, TK1, GMFB, DLGAP4, TYMS, USP4,DCK, MAD2L1, CDC40, RABIF, CXCL10, FAS, HNRPA3P1, SLC25A11, NDUFA9,C17orf25, ME2, CXCL11, SLC4A4, RBM25, AK2, hCAP-D3, SOCS6, DDAH2, RBBP4,AGPAT5, DKFZp762E1312, SEC10L1, PBK, PSAT1, HNRPD, BRIP1, ETNK1, STAT1212 HNRPD, WARS, EPAS1, STAT1, EIF4E, 81% 83% 85% 76% 77% 79% MTHFD2,GBP1, TK1, GMFB, DLGAP4, TYMS, LMAN1, DCK, CDC40, CXCL9, IRF8, CXCL10,FAS, PLK4, HNRPA3P1, SLC25A11, NDUFA9, KPNB1, WHSC1, CA2, ME2, CXCL11,GZMB, RBBP4, SLC4A4, RBM25, NUP210, DDAH2, PBK, KLHL24, ETNK1 213 HNRPD,WARS, SFRS2, STAT1, EIF4E, 100% 90% 92% 72% 85% 79% PRDX3, MTHFD2, GMFB,DLGAP4, TYMS, DCK, ARF6, CDC40, CXCL9, IRF8, CXCL10, FAS, TRIM25,SLC25A11, C1QBP, C17orf25, CA2, ME2, CXCL11, GZMB, IFT20, TLK1, RBM25,AK2, CDC42BPA, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, ETNK1 214 WARS,EIF4E, MTHFD2, PSME2, TK1, 81% 79% 85% 79% 85% 72% GMFB, DLGAP4, TYMS,USP4, CDC40, CXCL9, IRF8, GTSE1, CXCL10, FAS, PLK4, TRIM25, C1QBP,SLC25A11, C17orf25, CA2, HNRPD, ME2, CXCL11, IFT20, AK2, BRRN1, SOCS6,CDC42BPA, SFRS2, RBBP4, MARCH5, SEC10L1, FLJ13220, PSAT1, BRIP1, TRMT5,KLHL24, STAT1 215 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 85% 86% 88% 72% 81%72% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, MAD2L1, CDC40, CXCL9, IRF8,GTSE1, CXCL10, SLC25A11, NDUFA9, WHSC1, CA2, ME2, CXCL11, IFT20, RBM25,AK2, BRRN1, CDC42BPA, FAS, RBBP4, BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK,BRIP1, KLHL24, ETNK1, STAT1 216 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 73%83% 88% 79% 85% 72% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, TES, CTSS,LMAN1, CDC40, CXCL9, IRF8, CXCL10, FAS, PLK4, HNRPA3P1, KITLG, C1QBP,NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11, RBM25, AK2, hCAP-D3, BAZ1A, AGPAT5, DKFZp762E1312, PBK, BRIP1 217 WARS, EIF4E, MTHFD2,PSME2, MCM6, 85% 86% 81% 79% 77% 76% DLGAP4, TYMS, USP4, TES, DCK, ARF6,MAD2L1, CDC40, CXCL9, IRF8, CXCL10, PLK4, HNRPA3P1, TRIM25, SLC25A11,C1QBP, WHSC1, CA2, ME2, CXCL11, GZMB, IFT20, TLK1, SLC4A4, RBM25, SOCS6,DDAH2, FAS, FLJ13220, PBK, KLHL24, ETNK1, STAT1 218 WARS, SFRS2, EPAS1,STAT1, PAICS, 81% 83% 85% 83% 88% 76% PRDX3, MTHFD2, PSME2, MCM6, GMFB,DLGAP4, TYMS, USP4, TES, LMAN1, SLC4A4, CXCL9, IRF8, CXCL10, FAS, PLK4,CHEK1, HNRPA3P1, TRIM25, C1QBP, NDUFA9, CA2, ME2, FUT4, CXCL11, RBM25,AK2, ATP5A1, AGPAT5, SEC10L1, FLJ13220, HNRPD, KLHL24 219 WARS, SFRS2,EIF4E, PRDX3, MTHFD2, 81% 79% 85% 79% 88% 76% PSME2, GBP1, GMFB, DLGAP4,TYMS, USP4, CDC40, CXCL9, CXCL10, FAS, PLK4, HNRPA3P1, SLC25A11, NDUFA9,WHSC1, C17orf25, CA2, ME2, CXCL11, IFT20, RBM25, hCAP-D3, ATP5A1, RBBP4,AGPAT5, FLJ10534, MARCH5, SEC10L1, HNRPD, BRIP1, KLHL24, STAT1 220HNRPD, WARS, SFRS2, EPAS1, SFPQ, 73% 79% 85% 79% 85% 83% PRDX3, MTHFD2,PSME2, GMFB, TYMS, USP4, TES, LMAN1, CDC40, CXCL9, CXCL10, FAS, C1QBP,SLC25A11, WHSC1, CA2, ME2, FUT4, TLK1, CXCL11, SLC4A4, RBM25, hCAP-D3,DDAH2, BAZ1A, FLJ10534, MARCH5, FLJ13220, PBK, PSAT1, BRIP1,TRMT5, STAT1221 HNRPD, EPAS1, STAT1, PRDX3, 81% 83% 88% 83% 85% 86% MTHFD2, PSME2,TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, CXCL9, CXCL10, FAS, CHEK1,HNRPA3P1, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, CA2, ME2, CXCL11, TLK1,RBM25, ATP5A1, DDAH2, RBBP4, SEC10L1, PBK, BRIP1, ETNK1 222 WARS, SFRS2,EIF4E, MTHFD2, PSME2, 88% 86% 92% 72% 81% 72% DLGAP4, TYMS, ARF6, CXCL9,IRF8, GTSE1, RABIF, CXCL10, FAS, PLK4, KITLG, SLC25A11, C1QBP, NDUFA9,ME2, CXCL11, GZMB, IFT20, RBBP4, SLC4A4, RBM25, AK2, BAZ1A, AGPAT5,MARCH5, FLJ13220, HNRPD, BRIP1, KLHL24, ETNK1, STAT1 223 HNRPD, WARS,SFRS2, STAT1, EIF4E, 85% 83% 88% 76% 81% 83% MTHFD2, PSME2, GMFB,DLGAP4, TYMS, LMAN1, ARF6, CXCL9, GTSE1, CXCL10, FAS, PLK4, HNRPA3P1,TRIM25, KITLG, C1QBP, SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11, TLK1,RBM25, ATP5A1, AGPAT5, FLJ10534, MARCH5, FLJ13220, PBK, BRIP1, TRMT5 224HNRPD, WARS, SFRS2, EIF4E, PRDX3, 85% 79% 92% 76% 85% 72% MTHFD2, PSME2,GMFB, DLGAP4, TYMS, USP4, TES, CDC40, SLC4A4, CXCL9, CXCL10, FAS,TRIM25, KITLG, C1QBP, NDUFA9, C17orf25, CA2, ME2, GZMB, TLK1, CXCL11,RBM25, CAMSAP1L1, CDC42BPA, DDAH2, BAZ1A, AGPAT5, SEC10L1, PBK, KLHL24,ETNK1, STAT1 225 WARS, EIF4E, PRDX3, MTHFD2, PSME2, 81% 79% 88% 76% 88%79% GMFB, DLGAP4, TYMS, USP4, CTSS, ARF6, CDC40, CXCL9, IRF8, CXCL10,FAS, PLK4, CHEK1, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, HNRPD,ME2, CXCL11, GZMB, IFT20, RBBP4, SLC4A4, RBM25, ATP5A1, PBK, BRIP1,TRMT5, STAT1 226 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 77% 79% 77% 86% 73%69% PSME2, GMFB, DLGAP4, TYMS, LMAN1, DCK, CXCL9, CXCL10, FAS, HNRPA3P1,TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2, SLC4A4, CXCL11, RBM25,BRRN1, BAZ1A, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1,BRIP1, TRMT5, ETNK1, STAT1 227 HNRPD, WARS, SFRS2, EPAS1, PRDX3, 81% 90%92% 76% 88% 69% PSME2, GBP1, TK1, DLGAP4, TYMS, DCK, ARF6, CDC40, CXCL9,GTSE1, RABIF, CXCL10, FAS, TRIM25, C1QBP, NDUFA9, SLC25A11, C17orf25,CA2, ME2, CXCL11, GZMB, IFT20, RBBP4, RBM25, AGPAT5, MARCH5, SEC10L1,FLJ13220, PBK, BRIP1, STAT1 228 WARS, SFRS2, EPAS1, STAT1, EIF4E, 77%83% 88% 76% 88% 76% MTHFD2, GMFB, DLGAP4, TYMS, TES, CTSS, CXCL9,CXCL10, FAS, PLK4, CHEK1, TRIM25, SLC25A11, NDUFA9, WHSC1, C17orf25,CA2, ME2, FUT4, CXCL11, SLC4A4, RBM25, AK2, BRRN1, CDC42BPA, DDAH2,AGPAT5, MARCH5, PBK, HNRPD, KLHL24 229 HNRPD, WARS, SFRS2, EPAS1, PAICS,85% 86% 85% 72% 85% 76% EIF4E, PRDX3, MTHFD2, PSME2, DLGAP4, TYMS,CXCL9, IRF8, RABIF, FAS, PLK4, TRIM25, SLC25A11, C1QBP, WHSC1, C17orf25,CA2, ME2, FUT4, CXCL11, GZMB, IFT20, RBM25, SOCS6, DDAH2, MARCH5, PBK,PSAT1, BRIP1, TRMT5, STAT1 230 WARS, SFRS2, STAT1, MTHFD2, PSME2, 73%83% 81% 76% 69% 66% GMFB, DLGAP4, TYMS, USP4, TES, ARF6, CDC40, CXCL9,CXCL10, FAS, HNRPA3P1, C1QBP, SLC25A11, WHSC1, ME2, CXCL11, RBBP4,SLC4A4, RBM25, AK2, hCAP-D3, CDC42BPA, FLJ10534, SEC10L1, FLJ13220, PBK,PSAT1, HNRPD, BRIP1, TRMT5, KLHL24 231 SFRS2, EPAS1, EIF4E, MTHFD2,PSME2, 73% 76% 92% 72% 77% 76% MCM6, TK1, GMFB, DLGAP4, TYMS, CTSS,LMAN1, CXCL9, IRF8, CXCL10, CHEK1, HNRPA3P1, KITLG, SLC25A11, C1QBP,NDUFA9, WHSC1, C17orf25, ME2, FUT4, CXCL11, GZMB, RBM25, CDC42BPA, FAS,RBBP4, AGPAT5, FLJ10534, SEC10L1, FLJ13220, PBK, HNRPD, TRMT5, STAT1 232HNRPD, WARS, SFRS2, PAICS, EIF4E, 73% 79% 88% 86% 81% 83% MTHFD2, PSME2,MCM6, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, TES, CDC40, CXCL9, IRF8,RABIF, CXCL10, CHEK1, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, FUT4,CXCL11, IFT20, TLK1, SLC4A4, RBM25, NUP210, CAMSAP1L1, BRRN1, FAS,RBBP4, BAZ1A, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, KLHL24,STAT1 233 WARS, EIF4E, PRDX3, MTHFD2, PSME2, 77% 79% 92% 76% 88% 76%GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, DCK, ARF6, MAD2L1, CDC40, SLC4A4,CXCL9, GTSE1, CXCL10, FAS, KITLG, NDUFA9, SLC25A11, WHSC1, C17orf25,CA2, HNRPD, ME2, FUT4, CXCL11, GZMB, IFT20, TLK1, RBM25, AK2, CAMSAP1L1,DDAH2, RBBP4, BAZ1A, AGPAT5, SEC10L1, PBK, BRIP1, KLHL24, ETNK1, STAT1234 WARS, SFRS2, EPAS1, STAT1, PAICS, 85% 90% 92% 79% 77% 83% EIF4E,PRDX3, MTHFD2, PSME2, GBP1, GMFB, DLGAP4, TYMS, ARF6, CDC40, CXCL9,IRF8, RABIF, CXCL10, FAS, SLC25A11, NDUFA9, C17orf25, CA2, ME2, CXCL11,GZMB, IFT20, RBBP4, TLK1, SLC4A4, RBM25, NUP210, BRRN1, ATP5A1, AGPAT5,MARCH5, SEC10L1, PBK, PSAT1, HNRPD, BRIP1, TRMT5 235 WARS, SFRS2, EPAS1,STAT1, EIF4E, 81% 90% 92% 76% 85% 69% PRDX3, MTHFD2, PSME2, GMFB,DLGAP4, TYMS, USP4, CTSS, DCK, ARF6, MAD2L1, CDC40, CXCL9, CXCL10, PLK4,CHEK1, TRIM25, KITLG, SLC25A11, C1QBP, KPNB1, WHSC1, C17orf25, CA2,HNRPD, ME2, GZMB, CXCL11, RBM25, BRRN1, ATP5A1, CDC42BPA, DDAH2, FAS,BAZ1A, AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, TRMT5, KLHL24, ETNK1 236HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 83% 88% 72% 81% 76% MTHFD2, PSME2,TK1, GMFB, DLGAP4, TYMS, USP4, TES, CTSS, DCK, ARF6, MAD2L1, CDC40,CXCL9, RABIF, CXCL10, CHEK1, HNRPA3P1, TRIM25, KITLG, C1QBP, NDUFA9,KPNB1, SLC25A11, WHSC1, CA2, ME2, GZMB, SLC4A4, CXCL11, RBM25, AK2,ATP5A1, DDAH2, FAS, BAZ1A, DKFZp762E1312, SEC10L1, FLJ13220, BRIP1,TRMT5, ETNK1, STAT1 237 WARS, SFRS2, PAICS, EIF4E, PRDX3, 77% 83% 92%83% 81% 76% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, DCK, ARF6,MAD2L1, SLC4A4, CXCL9, GTSE1, CXCL10, FAS, HNRPA3P1, KITLG, SLC25A11,C1QBP, NDUFA9, KPNB1, C17orf25, CA2, HNRPD, ME2, CXCL11, GZMB, IFT20,RBBP4, RBM25, AK2, ATP5A1, BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK, BRIP1,ETNK1, STAT1 238 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 85% 86% 88% 86% 85%79% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, SLC4A4,CXCL9, IRF8, GTSE1, CXCL10, CHEK1, TRIM25, KITLG, SLC25A11, C1QBP,NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2, FUT4, TLK1, CXCL11, RBM25,BRRN1, DDAH2, FAS, RBBP4, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220,PBK, TRMT5, STAT1 239 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 69% 79% 88% 83%81% 76% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, DCK, CDC40,CXCL9, IRF8, GTSE1, RABIF, CXCL10, FAS, CHEK1, SLC25A11, C1QBP, NDUFA9,WHSC1, C17orf25, CA2, ME2, IFT20, CXCL11, SLC4A4, RBM25, AK2, hCAP-D3,ATP5A1, SOCS6, DDAH2, FLJ10534, MARCH5, SEC10L1, PBK, PSAT1, BRIP1,STAT1 240 WARS, SFRS2, EPAS1, STAT1, EIF4E, 81% 83% 96% 69% 81% 76%PRDX3, MTHFD2, TK1, GMFB, DLGAP4, TYMS, CTSS, LMAN1, ARF6, MAD2L1,CXCL9, IRF8, RABIF, CXCL10, FAS, HNRPA3P1, TRIM25, KITLG, C1QBP, NDUFA9,SLC25A11, WHSC1, C17orf25, HNRPD, ME2, GZMB, SLC4A4, CXCL11, RBM25, AK2,CAMSAP1L1, hCAP-D3, BRRN1, CDC42BPA, RBBP4, BAZ1A, FLJ10534, SEC10L1,BRIP1, KLHL24, ETNK1 241 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 73% 79% 88%83% 92% 79% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, LMAN1, MAD2L1,CDC40, CXCL9, RABIF, CXCL10, FAS, PLK4, TRIM25, SLC25A11, NDUFA9, KPNB1,WHSC1, CA2, ME2, CXCL11, TLK1, SLC4A4, RBM25, hCAP-D3, BRRN1, SOCS6,CDC42BPA, DDAH2, RBBP4, BAZ1A, AGPAT5, DKFZp762E1312, SEC10L1, PBK,BRIP1, KLHL24, ETNK1, STAT1 242 WARS, STAT1, EIF4E, MTHFD2, PSME2, 81%83% 85% 79% 81% 69% TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1, DCK,ARF6, MAD2L1, CDC40, CXCL9, RABIF, CXCL10, FAS, PLK4, TRIM25, KITLG,SLC25A11, C1QBP, NDUFA9, KPNB1, C17orf25, CA2, ME2, CXCL11, GZMB,SLC4A4, RBM25, AK2, hCAP-D3, DDAH2, RBBP4, BAZ1A, PSAT1, HNRPD, BRIP1,TRMT5, KLHL24, ETNK1 243 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 85% 83% 92%79% 77% 72% PSME2, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1, CDC40, SLC4A4,CXCL9, CXCL10, FAS, PLK4, CHEK1, KITLG, C1QBP, NDUFA9, WHSC1, CA2,HNRPD, ME2, CXCL11, GZMB, TLK1, RBM25, AK2, hCAP-D3, BRRN1, CDC42BPA,RBBP4, BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, ETNK1,STAT1 244 WARS, SFRS2, EPAS1, STAT1, EIF4E, 81% 83% 88% 79% 81% 69%PRDX3, MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, ARF6, CDC40,SLC4A4, CXCL9, RABIF, CXCL10, FAS, PLK4, CHEK1, KITLG, SLC25A11, C1QBP,NDUFA9, WHSC1, CA2, HNRPD, ME2, CXCL11, GZMB, IFT20, RBM25, CAMSAP1L1,BRRN1, CDC42BPA, BAZ1A, AGPAT5, FLJ10534, DKFZp762E1312, PBK, ETNK1 245HNRPD, WARS, SFRS2, EPAS1, PAICS, 77% 86% 88% 76% 77% 76% EIF4E, PRDX3,MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, TES, DCK, CDC40, SLC4A4, CXCL9,CXCL10, PLK4, CHEK1, HNRPA3P1, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1,CA2, ME2, GZMB, RBBP4, CXCL11, RBM25, AK2, NUP210, CAMSAP1L1, hCAP-D3,CDC42BPA, FAS, MARCH5, SEC10L1, PBK, ETNK1, STAT1 246 WARS, SFRS2,EPAS1, EIF4E, PRDX3, 77% 83% 92% 79% 81% 79% MTHFD2, PSME2, GBP1, GMFB,DLGAP4, TYMS, TES, LMAN1, CDC40, SLC4A4, CXCL9, RABIF, CXCL10, FAS,PLK4, HNRPA3P1, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2,ME2, FUT4, GZMB, TLK1, CXCL11, RBM25, CAMSAP1L1, DDAH2, AGPAT5, MARCH5,SEC10L1, FLJ13220, PBK, HNRPD, BRIP1, ETNK1, STAT1 247 WARS, SFRS2,EPAS1, EIF4E, PRDX3, 77% 83% 85% 79% 85% 72% MTHFD2, PSME2, GBP1, GMFB,DLGAP4, TYMS, USP4, TES, MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, GTSE1,CXCL10, PLK4, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25,CA2, ME2, IFT20, RBBP4, CXCL11, RBM25, AK2, CAMSAP1L1, CDC42BPA, FAS,AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, HNRPD, BRIP1, KLHL24, ETNK1,STAT1 248 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 77% 86% 88% 76% 81% 69%MTHFD2, PSME2, MCM6, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, DCK, CDC40,CXCL9, GTSE1, RABIF, CXCL10, FAS, PLK4, TRIM25, C1QBP, NDUFA9, SLC25A11,WHSC1, C17orf25, CA2, ME2, FUT4, GZMB, IFT20, RBBP4, CXCL11, SLC4A4,RBM25, BRRN1, AGPAT5, FLJ10534, MARCH5, FLJ13220, PSAT1, TRMT5, KLHL24,ETNK1, STAT1 249 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 92% 97% 88% 76% 85%79% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, MAD2L1, SLC4A4, CXCL9,GTSE1, CXCL10, FAS, PLK4, TRIM25, KITLG, NDUFA9, KPNB1, WHSC1, C17orf25,CA2, ME2, FUT4, CXCL11, GZMB, IFT20, TLK1, RBM25, CAMSAP1L1, BRRN1,SOCS6, CDC42BPA, BAZ1A, AGPAT5, MARCH5, SEC10L1, FLJ13220, KLHL24,ETNK1, STAT1 250 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 92% 90% 92% 76% 85%79% SFPQ, PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, ARF6, CDC40,CXCL9, CXCL10, FAS, CHEK1, TRIM25, NDUFA9, KPNB1, SLC25A11, C17orf25,CA2, ME2, CXCL11, IFT20, TLK1, SLC4A4, RBM25, AK2, BRRN1, ATP5A1, DDAH2,BAZ1A, AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, STAT1 251WARS, EPAS1, STAT1, EIF4E, SFPQ, 77% 90% 92% 76% 85% 72% PRDX3, MTHFD2,PSME2, TK1, GMFB, DLGAP4, TYMS, LMAN1, ARF6, SLC4A4, CXCL9, IRF8, GTSE1,CXCL10, FAS, PLK4, HNRPA3P1, SLC25A11, C1QBP, NDUFA9, CA2, HNRPD, ME2,FUT4, CXCL11, GZMB, IFT20, TLK1, RBM25, AK2, ATP5A1, SOCS6, DDAH2,RBBP4, AGPAT5, MARCH5, SEC10L1, FLJ13220, BRIP1, TRMT5 252 WARS, SFRS2,EPAS1, PAICS, EIF4E, 65% 83% 77% 90% 73% 76% PRDX3, MTHFD2, PSME2, GBP1,GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, CDC40, SLC4A4, GTSE1, RABIF,CXCL10, FAS, PLK4, HNRPA3P1, C1QBP, SLC25A11, WHSC1, HNRPD, ME2, FUT4,CXCL11, IFT20, TLK1, RBM25, AK2, NUP210, BRRN1, ATP5A1, AGPAT5,FLJ10534, DKFZp762E1312, SEC10L1, FLJ13220, PBK, TRMT5, KLHL24, ETNK1,STAT1 253 HNRPD, WARS, EPAS1, STAT1, EIF4E, 73% 83% 85% 79% 81% 76%PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, DCK, SLC4A4,CXCL9, CXCL10, FAS, PLK4, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1,C17orf25, CA2, ME2, FUT4, CXCL11, RBBP4, TLK1, RBM25, CAMSAP1L1, ATP5A1,MARCH5, SEC10L1, PBK, PSAT1, BRIP1, TRMT5, KLHL24, ETNK1 254 HNRPD,WARS, EPAS1, EIF4E, MTHFD2, 77% 76% 92% 86% 88% 79% PSME2, MCM6, GBP1,GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, ARF6, SLC4A4, CXCL9, IRF8, CXCL10,FAS, PLK4, CHEK1, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25,CA2, ME2, FUT4, IFT20, RBBP4, CXCL11, RBM25, NUP210, hCAP-D3, SFRS2,DDAH2, BAZ1A, AGPAT5, FLJ10534, DKFZp762E1312, SEC10L1, FLJ13220,KLHL24, STAT1 255 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 79% 85% 79% 85%76% PRDX3, MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, LMAN1, CDC40,CXCL9, CXCL10, PLK4, CHEK1, TRIM25, KITLG, C1QBP, NDUFA9, WHSC1,C17orf25, CA2, ME2, CXCL11, SLC4A4, RBM25, AK2, NUP210, DDAH2, FAS,BAZ1A, AGPAT5, FLJ10534, MARCH5, DKFZp762E1312, SEC10L1, PBK, PSAT1,BRIP1, KLHL24, STAT1 256 WARS, SFRS2, EPAS1, STAT1, EIF4E, 77% 83% 85%79% 81% 83% SFPQ, PRDX3, MTHFD2, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1,ARF6, CDC40, SLC4A4, CXCL9, RABIF, CXCL10, FAS, PLK4, CHEK1, TRIM25,KITLG, SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, ME2, TLK1, RBM25, NUP210,AGPAT5, FLJ10534, SEC10L1, FLJ13220, PBK, PSAT1, HNRPD, BRIP1, TRMT5,KLHL24 257 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 73% 86% 88% 83% 77% 72%GBP1, TK1, GMFB, DLGAP4, TYMS, LMAN1, MAD2L1, CDC40, CXCL9, CXCL10, FAS,CHEK1, HNRPA3P1, KITLG, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, CA2,HNRPD, ME2, GZMB, TLK1, SLC4A4, CXCL11, RBM25, AK2, CAMSAP1L1, DDAH2,AGPAT5, FLJ10534, MARCH5, DKFZp762E1312, PBK, PSAT1, BRIP1, TRMT5,KLHL24, ETNK1, STAT1 258 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 77% 83% 73%86% 73% 76% PSME2, TK1, GMFB, DLGAP4, TYMS, LMAN1, ARF6, CDC40, CXCL9,CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, SLC25A11, C1QBP, NDUFA9, WHSC1,C17orf25, HNRPD, ME2, CXCL11, IFT20, RBBP4, SLC4A4, RBM25, AK2, ATP5A1,SOCS6, FLJ10534, MARCH5, DKFZp762E1312, SEC10L1, FLJ13220, PBK, PSAT1,BRIP1, TRMT5, ETNK1, STAT1 259 HNRPD, WARS, EPAS1, PAICS, MTHFD2, 85%93% 92% 72% 77% 72% PSME2, MCM6, GMFB, DLGAP4, TYMS, CDC40, CXCL9,RABIF, CXCL10, FAS, PLK4, HNRPA3P1, TRIM25, SLC25A11, C1QBP, NDUFA9,WHSC1, CA2, ME2, CXCL11, GZMB, IFT20, RBBP4, TLK1, RBM25, AK2,CAMSAP1L1, ATP5A1, CDC42BPA, DDAH2, BAZ1A, AGPAT5, FLJ10534, MARCH5,SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, ETNK1, STAT1 260 HNRPD, WARS,SFRS2, PAICS, EIF4E, 77% 79% 85% 76% 85% 69% PRDX3, MTHFD2, PSME2, GMFB,DLGAP4, TYMS, ARF6, MAD2L1, CDC40, CXCL9, GTSE1, RABIF, CXCL10, PLK4,CHEK1, HNRPA3P1, TRIM25, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2,FUT4, CXCL11, IFT20, SLC4A4, RBM25, AK2, NUP210, ATP5A1, SOCS6, FAS,AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, PSAT1, BRIP1, ETNK1, STAT1 261HNRPD, WARS, SFRS2, STAT1, MTHFD2, 85% 83% 88% 72% 77% 76% TK1, GMFB,DLGAP4, TYMS, USP4, CTSS, ARF6, SLC4A4, CXCL9, GTSE1, CXCL10, FAS,HNRPA3P1, TRIM25, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2,ME2, CXCL11, GZMB, IFT20, RBM25, hCAP-D3, ATP5A1, SOCS6, DDAH2, BAZ1A,MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, ETNK1 262 HNRPD, WARS,SFRS2, EPAS1, EIF4E, 77% 79% 85% 79% 85% 76% MTHFD2, PSME2, TK1, GMFB,DLGAP4, TYMS, USP4, LMAN1, DCK, CDC40, CXCL9, CXCL10, FAS, PLK4, CHEK1,HNRPA3P1, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2,CXCL11, IFT20, SLC4A4, RBM25, AK2, ATP5A1, SOCS6, BAZ1A, AGPAT5,FLJ10534, SEC10L1, PBK, PSAT1, BRIP1, KLHL24, ETNK1, STAT1 263 HNRPD,WARS, SFRS2, EPAS1, STAT1, 81% 83% 88% 79% 81% 79% EIF4E, PRDX3, PSME2,MCM6, GBP1, GMFB, DLGAP4, USP4, CTSS, ARF6, CDC40, SLC4A4, CXCL9, GTSE1,RABIF, CXCL10, FAS, CHEK1, HNRPA3P1, KITLG, C1QBP, NDUFA9, KPNB1, WHSC1,CA2, ME2, CXCL11, RBM25, CDC42BPA, RBBP4, AGPAT5, MARCH5, SEC10L1,FLJ13220, PBK, PSAT1, TRMT5, KLHL24 264 WARS, SFRS2, EPAS1, EIF4E, SFPQ,88% 86% 88% 83% 85% 79% PRDX3, MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4,TYMS, CTSS, LMAN1, CDC40, SLC4A4, CXCL9, IRF8, CXCL10, FAS, PLK4,TRIM25, SLC25A11, C1QBP, NDUFA9, WHSC1, CA2, HNRPD, ME2, CXCL11, GZMB,TLK1, RBM25, AK2, hCAP-D3, ATP5A1, CDC42BPA, BAZ1A, AGPAT5, MARCH5,SEC10L1, PBK, TRMT5, KLHL24, STAT1 265 HNRPD, WARS, EPAS1, PAICS, EIF4E,92% 90% 85% 76% 69% 76% SFPQ, PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4,TYMS, USP4, CTSS, LMAN1, ARF6, CDC40, SLC4A4, CXCL9, IRF8, CXCL10, FAS,PLK4, CHEK1, TRIM25, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, ME2,GZMB, TLK1, CXCL11, RBM25, AK2, CAMSAP1L1, AGPAT5, FLJ10534, SEC10L1,PBK, BRIP1, KLHL24, STAT1 266 WARS, SFRS2, EPAS1, EIF4E, PRDX3, 77% 86%88% 76% 85% 79% MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, TES, CTSS,MAD2L1, SLC4A4, CXCL9, IRF8, CXCL10, FAS, PLK4, TRIM25, C1QBP, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, ME2, CXCL11, GZMB, RBM25, AK2, ATP5A1,RBBP4, AGPAT5, MARCH5, SEC10L1, PBK, HNRPD, BRIP1, TRMT5, KLHL24, ETNK1,STAT1 267 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 85% 83% 85% 79% 81% 76%PSME2, GMFB, DLGAP4, TYMS, TES, LMAN1, DCK, ARF6, CDC40, SLC4A4, CXCL9,IRF8, GTSE1, CXCL10, FAS, CHEK1, SLC25A11, C1QBP, NDUFA9, WHSC1,C17orf25, CA2, ME2, CXCL11, IFT20, RBM25, AK2, NUP210, SOCS6, CDC42BPA,SFRS2, RBBP4, BAZ1A, FLJ10534, MARCH5, FLJ13220, PBK, PSAT1, HNRPD,KLHL24, STAT1 268 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 88% 93% 92% 76% 81%72% PRDX3, MTHFD2, PSME2, MCM6, GBP1, GMFB, DLGAP4, TYMS, USP4, ARF6,CDC40, SLC4A4, IRF8, GTSE1, CXCL10, FAS, HNRPA3P1, TRIM25, KITLG,NDUFA9, SLC25A11, CA2, ME2, CXCL11, GZMB, TLK1, RBM25, AK2, hCAP-D3,CDC42BPA, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1,BRIP1, TRMT5, STAT1 269 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 81% 79% 92%76% 81% 69% MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, USP4, ARF6,CDC40, SLC4A4, CXCL9, GTSE1, CXCL10, HNRPA3P1, KITLG, C1QBP, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, ME2, FUT4, CXCL11, GZMB, RBM25, AK2,CDC42BPA, FAS, RBBP4, BAZ1A, SEC10L1, FLJ13220, PBK, PSAT1, KLHL24,ETNK1, STAT1 270 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 88% 86% 88% 79% 85%72% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, CTSS, ARF6, MAD2L1,CDC40, CXCL9, IRF8, GTSE1, CXCL10, FAS, CHEK1, HNRPA3P1, TRIM25, KITLG,SLC25A11, NDUFA9, KPNB1, WHSC1, CA2, ME2, FUT4, CXCL11, GZMB, RBM25,AK2, CDC42BPA, BAZ1A, AGPAT5, DKFZp762E1312, SEC10L1, PBK, TRMT5,KLHL24, ETNK1, STAT1 271 WARS, SFRS2, EPAS1, STAT1, EIF4E, 77% 69% 92%79% 81% 69% MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1,ARF6, MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, GTSE1, CXCL10, PLK4, C1QBP,NDUFA9, SLC25A11, WHSC1, CA2, HNRPD, ME2, FUT4, GZMB, RBM25, AK2,ATP5A1, CDC42BPA, FAS, AGPAT5, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1,TRMT5, KLHL24, ETNK1 272 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 73% 83% 92%83% 85% 76% PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, CTSS,LMAN1, DCK, SLC4A4, CXCL9, IRF8, CXCL10, FAS, HNRPA3P1, KITLG, C1QBP,NDUFA9, SLC25A11, CA2, ME2, FUT4, IFT20, RBBP4, TLK1, CXCL11, RBM25,BRRN1, CDC42BPA, AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, BRIP1, TRMT5,KLHL24, ETNK1, STAT1 273 WARS, SFRS2, EPAS1, STAT1, EIF4E, 88% 83% 85%83% 77% 79% MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, ARF6,CXCL9, IRF8, RABIF, CXCL10, FAS, PLK4, CHEK1, KITLG, SLC25A11, C1QBP,NDUFA9, WHSC1, CA2, ME2, CXCL11, IFT20, RBBP4, TLK1, RBM25, ATP5A1,CDC42BPA, FLJ13220, PBK, HNRPD, BRIP1, TRMT5, KLHL24, ETNK1 274 HNRPD,WARS, SFRS2, EPAS1, EIF4E, 81% 86% 88% 83% 85% 76% PRDX3, MTHFD2, PSME2,GBP1, GMFB, DLGAP4, TYMS, TES, DCK, MAD2L1, CXCL9, CXCL10, FAS, PLK4,HNRPA3P1, KITLG, SLC25A11, NDUFA9, WHSC1, C17orf25, CA2, ME2, IFT20,RBBP4, CXCL11, SLC4A4, RBM25, NUP210, CAMSAP1L1, BRRN1, CDC42BPA, DDAH2,AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, TRMT5, KLHL24, ETNK1,STAT1 275 WARS, SFRS2, PAICS, EIF4E, MTHFD2, 73% 86% 77% 83% 69% 79%PSME2, MCM6, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, TES, LMAN1, CDC40,CXCL9, CXCL10, PLK4, TRIM25, KITLG, SLC25A11, C1QBP, NDUFA9, C17orf25,HNRPD, ME2, CXCL11, IFT20, TLK1, SLC4A4, RBM25, hCAP-D3, ATP5A1, DDAH2,FAS, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,KLHL24, STAT1 276 HNRPD, WARS, SFRS2, STAT1, EIF4E, 85% 79% 88% 79% 81%79% PRDX3, MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, USP4, DCK,ARF6, CDC40, CXCL9, IRF8, CXCL10, FAS, PLK4, TRIM25, KITLG, C1QBP,NDUFA9, SLC25A11, WHSC1, CA2, ME2, CXCL11, GZMB, RBBP4, TLK1, RBM25,AK2, NUP210, ATP5A1, AGPAT5, MARCH5, SEC10L1, PBK, BRIP1, TRMT5 277HNRPD, WARS, SFRS2, EPAS1, STAT1, 81% 83% 88% 76% 77% 69% EIF4E, PRDX3,MTHFD2, PSME2, MCM6, GBP1, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, DCK,SLC4A4, CXCL9, GTSE1, CXCL10, PLK4, CHEK1, TRIM25, C1QBP, NDUFA9, KPNB1,WHSC1, C17orf25, ME2, CXCL11, RBM25, BRRN1, ATP5A1, CDC42BPA, DDAH2,FAS, AGPAT5, MARCH5, PBK, BRIP1, TRMT5, KLHL24, ETNK1 278 WARS, STAT1,EIF4E, SFPQ, PRDX3, 77% 72% 88% 83% 77% 79% MTHFD2, MCM6, TK1, GMFB,DLGAP4, TYMS, TES, CTSS, MAD2L1, CDC40, SLC4A4, CXCL9, RABIF, CXCL10,FAS, KITLG, SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, HNRPD, ME2, GZMB,TLK1, CXCL11, RBM25, BRRN1, CDC42BPA, SFRS2, DDAH2, AGPAT5, SEC10L1,PBK, PSAT1, BRIP1, TRMT5, KLHL24 279 HNRPD, WARS, EPAS1, STAT1, EIF4E,77% 86% 92% 76% 77% 76% SFPQ, PRDX3, MTHFD2, PSME2, MCM6, TK1, GMFB,DLGAP4, TYMS, USP4, TES, DCK, ARF6, CDC40, SLC4A4, CXCL9, RABIF, CXCL10,FAS, TRIM25, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, ME2, GZMB, TLK1,CXCL11, RBM25, AK2, hCAP-D3, CDC42BPA, DDAH2, RBBP4, FLJ10534, SEC10L1,FLJ13220, PBK, PSAT1, BRIP1, KLHL24 280 WARS, SFRS2, STAT1, EIF4E,MTHFD2, 81% 79% 92% 79% 85% 72% PSME2, MCM6, GBP1, TK1, GMFB, DLGAP4,TYMS, USP4, TES, CTSS, LMAN1, ARF6, CDC40, SLC4A4, CXCL9, CXCL10, FAS,PLK4, KITLG, C1QBP, KPNB1, WHSC1, CA2, ME2, FUT4, GZMB, CXCL11, RBM25,AK2, CDC42BPA, RBBP4, BAZ1A, AGPAT5, MARCH5, SEC10L1, PBK, HNRPD, BRIP1,KLHL24, ETNK1 281 HNRPD, WARS, SFRS2, EPAS1, STAT1, 85% 79% 77% 86% 73%76% EIF4E, PRDX3, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, CTSS, LMAN1,DCK, CDC40, SLC4A4, CXCL9, IRF8, CXCL10, TRIM25, SLC25A11, C1QBP,NDUFA9, KPNB1, WHSC1, ME2, CXCL11, TLK1, RBM25, hCAP-D3, CDC42BPA, FAS,BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK, TRMT5, ETNK1 282 HNRPD, WARS,SFRS2, EPAS1, EIF4E, 77% 83% 88% 83% 88% 86% PRDX3, MTHFD2, PSME2, GBP1,GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1, MAD2L1, SLC4A4, CXCL9, CXCL10,FAS, CHEK1, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2,FUT4, CXCL11, TLK1, RBM25, hCAP-D3, ATP5A1, CDC42BPA, DDAH2, AGPAT5,FLJ10534, DKFZp762E1312, SEC10L1, FLJ13220, PBK, TRMT5, STAT1 283 WARS,SFRS2, PAICS, EIF4E, PRDX3, 81% 83% 85% 76% 85% 72% MTHFD2, PSME2, TK1,GMFB, DLGAP4, TYMS, USP4, TES, ARF6, CDC40, CXCL9, CXCL10, FAS, PLK4,TRIM25, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, CA2, ME2, FUT4, IFT20,SLC4A4, CXCL11, RBM25, AK2, BRRN1, ATP5A1, CDC42BPA, AGPAT5, MARCH5,SEC10L1, FLJ13220, PBK, HNRPD, BRIP1, TRMT5, KLHL24, ETNK1, STAT1 284HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 76% 88% 79% 85% 72% PRDX3, MTHFD2,PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, SLC4A4, CXCL9,IRF8, CXCL10, FAS, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2,ME2, GZMB, CXCL11, RBM25, AK2, hCAP-D3, CDC42BPA, DDAH2, RBBP4, AGPAT5,MARCH5, DKFZp762E1312, SEC10L1, FLJ13220, PBK, BRIP1, TRMT5, KLHL24,STAT1 285 WARS, SFRS2, EPAS1, STAT1, EIF4E, 85% 86% 92% 76% 81% 72%PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, ARF6, CDC40,SLC4A4, CXCL9, CXCL10, FAS, CHEK1, TRIM25, SLC25A11, C1QBP, C17orf25,CA2, ME2, GZMB, IFT20, RBBP4, CXCL11, RBM25, AK2, NUP210, SOCS6, DDAH2,AGPAT5, FLJ10534, MARCH5, DKFZp762E1312, SEC10L1, PBK, HNRPD, TRMT5 286WARS, EPAS1, STAT1, PAICS, EIF4E, 73% 76% 81% 79% 73% 66% PRDX3, MTHFD2,PSME2, TK1, DLGAP4, TYMS, MAD2L1, CDC40, CXCL9, IRF8, CXCL10, FAS,TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, HNRPD, ME2,CXCL11, IFT20, RBBP4, SLC4A4, RBM25, AK2, NUP210, SOCS6, CDC42BPA,BAZ1A, AGPAT5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, TRMT5 287 WARS,SFRS2, EPAS1, EIF4E, PRDX3, 88% 90% 88% 79% 77% 79% PSME2, GMFB, DLGAP4,TYMS, CTSS, ARF6, MAD2L1, CDC40, CXCL9, CXCL10, FAS, TRIM25, SLC25A11,C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, GZMB,IFT20, TLK1, SLC4A4, RBM25, CAMSAP1L1, hCAP-D3, RBBP4, BAZ1A, AGPAT5,MARCH5, FLJ13220, PBK, TRMT5, ETNK1, STAT1 288 HNRPD, WARS, SFRS2,EPAS1, STAT1, 81% 90% 85% 76% 85% 69% EIF4E, SFPQ, PRDX3, MTHFD2, PSME2,TK1, GMFB, DLGAP4, TYMS, ARF6, CDC40, CXCL9, CXCL10, FAS, SLC25A11,NDUFA9, WHSC1, C17orf25, CA2, ME2, CXCL11, IFT20, SLC4A4, RBM25, AK2,SOCS6, DDAH2, RBBP4, BAZ1A, DKFZp762E1312, FLJ13220, PBK, PSAT1, BRIP1,ETNK1 289 WARS, SFRS2, EPAS1, STAT1, PAICS, 77% 86% 88% 83% 73% 69%EIF4E, PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1,CDC40, CXCL9, IRF8, RABIF, CXCL10, FAS, TRIM25, SLC25A11, C1QBP, WHSC1,C17orf25, CA2, HNRPD, ME2, CXCL11, GZMB, TLK1, RBM25, CAMSAP1L1,hCAP-D3, CDC42BPA, BAZ1A, AGPAT5, MARCH5, DKFZp762E1312, FLJ13220, PBK,PSAT1, BRIP1, KLHL24 290 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 85% 83% 85%83% 81% 72% PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, ARF6, MAD2L1, SLC4A4,CXCL9, IRF8, CXCL10, FAS, TRIM25, SLC25A11, NDUFA9, KPNB1, WHSC1,C17orf25, CA2, ME2, GZMB, IFT20, RBBP4, CXCL11, RBM25, AK2, BRRN1,CDC42BPA, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, HNRPD,BRIP1, KLHL24, ETNK1, STAT1 291 HNRPD, WARS, SFRS2, EPAS1, STAT1, 85%86% 92% 79% 85% 86% EIF4E, SFPQ, PRDX3, MTHFD2, GMFB, DLGAP4, TYMS,USP4, TES, CTSS, ARF6, MAD2L1, CDC40, CXCL9, CXCL10, FAS, PLK4, CHEK1,KITLG, SLC25A11, NDUFA9, KPNB1, CA2, ME2, FUT4, CXCL11, GZMB, TLK1,SLC4A4, RBM25, ATP5A1, DDAH2, MARCH5, DKFZp762E1312, PBK, BRIP1, KLHL24292 WARS, SFRS2, EPAS1, STAT1, EIF4E, 81% 83% 85% 72% 69% 76% PRDX3,MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, CXCL9, IRF8, RABIF,CXCL10, FAS, PLK4, TRIM25, C1QBP, NDUFA9, SLC25A11, C17orf25, CA2,HNRPD, ME2, CXCL11, GZMB, SLC4A4, RBM25, ATP5A1, CDC42BPA, DDAH2,MARCH5, DKFZp762E1312, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, KLHL24,ETNK1, UBD, GTSE1, MYO1B, TMED5, RBBP8 293 HNRPD, WARS, EIF4E, PRDX3,MTHFD2, 81% 79% 77% 79% 69% 72% PSME2, GMFB, DLGAP4, TYMS, USP4, MAD2L1,CXCL9, IRF8, CXCL10, FAS, SLC25A11, NDUFA9, WHSC1, ME2, CXCL11, IFT20,RBBP4, SLC4A4, RBM25, AK2, NUP210, CAMSAP1L1, ATP5A1, DDAH2, AGPAT5,MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, STAT1, FLJ22471, LAPTM5,DEPDC1, INDO, YDD19 294 WARS, SFRS2, PSME2, GMFB, DLGAP4, 73% 79% 88%79% 85% 76% TYMS, TES, CDC40, CXCL9, CXCL10, HNRPA3P1, C1QBP, SLC25A11,WHSC1, C17orf25, CA2, ME2, TLK1, SLC4A4, CXCL11, AK2, hCAP-D3, DDAH2,FAS, AGPAT5, FLJ10534, PSAT1, HNRPD, BRIP1, KLHL24, STAT1, IVD 295 WARS,SFRS2, EPAS1, EIF4E, SFPQ, 85% 86% 85% 76% 73% 76% MTHFD2, PSME2, TK1,GMFB, DLGAP4, TYMS, USP4, LMAN1, CDC40, SLC4A4, CXCL9, IRF8, RABIF,CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, TRIM25, SLC25A11, NDUFA9, KPNB1,WHSC1, CA2, HNRPD, ME2, GZMB, IFT20, CXCL11, RBM25, hCAP-D3, BAZ1A,AGPAT5, MARCH5, PBK, BRIP1, KLHL24, ETNK1, STAT1, TACC3, IL2RB, AK2 296HNRPD, WARS, SFRS2, PAICS, EIF4E, 81% 86% 92% 86% 85% 76% PRDX3, MTHFD2,PSME2, TK1, GMFB, DLGAP4, TYMS, CDC40, SLC4A4, CXCL9, CXCL10, HNRPA3P1,KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, FUT4, CXCL11, IFT20,RBBP4, RBM25, AK2, DDAH2, FAS, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1,TRMT5, KLHL24, STAT1, FEM1C, ITGB5 297 WARS, EIF4E, PSME2, GMFB, DLGAP4,77% 79% 73% 86% 81% 86% TYMS, USP4, CDC40, SLC4A4, CXCL10, TRIM25,C1QBP, NDUFA9, SLC25A11, CA2, ME2, CXCL11, RBM25, CAMSAP1L1, ATP5A1,SOCS6, FLJ10534, DKFZp762E1312, SEC10L1, HNRPD, STAT1, LMAN1, LOC92249,NFS1 298 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 81% 76% 81% 72% 77% 76%PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, TES, CTSS, DCK, MAD2L1, CXCL9,GTSE1, CXCL10, FAS, HNRPA3P1, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1,CA2, HNRPD, ME2, FUT4, CXCL11, SLC4A4, RBM25, CDC42BPA, DDAH2, RBBP4,FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, ETNK1, STAT1, ZWINT,ZG16, TPRT, PURA 299 HNRPD, WARS, STAT1, EIF4E, SFPQ, 85% 79% 81% 69%77% 72% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, MAD2L1, SLC4A4, CXCL9,CXCL10, FAS, NDUFA9, WHSC1, ME2, GZMB, TLK1, CXCL11, RBM25, AGPAT5,FLJ13220, KLHL24, SLAMF8, PBX1, CAP350 300 HNRPD, WARS, STAT1, EIF4E,PRDX3, 77% 79% 85% 76% 85% 79% MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4,TYMS, USP4, LMAN1, DCK, ARF6, CXCL9, CXCL10, FAS, TRIM25, KITLG, C1QBP,NDUFA9, KPNB1, SLC25A11, WHSC1, CA2, ME2, FUT4, CXCL11, GZMB, IFT20,SLC4A4, RBM25, BRRN1, ATP5A1, SFRS2, DDAH2, RBBP4, SEC10L1, FLJ13220,PBK, PSAT1, KLHL24, ETNK1, FLJ20273, VAPB, LARP4, CD74, BTN2A2 301 WARS,SFRS2, EPAS1, EIF4E, SFPQ, 81% 76% 88% 69% 77% 69% PRDX3, MTHFD2, PSME2,TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, CDC40, SLC4A4, CXCL9, IRF8, CXCL10,FAS, PLK4, CHEK1, TRIM25, KITLG, SLC25A11, C1QBP, NDUFA9, WHSC1, HNRPD,ME2, CXCL11, GZMB, RBBP4, RBM25, CAMSAP1L1, BRRN1, CDC42BPA, AGPAT5,FLJ10534, SEC10L1, PBK, BRIP1, KLHL24, ETNK1, STAT1, H2AFZ, PGGT1B 302WARS, EIF4E, MTHFD2, PSME2, GBP1, 85% 86% 88% 83% 81% 79% GMFB, DLGAP4,TYMS, CDC40, SLC4A4, CXCL10, FAS, CHEK1, HNRPA3P1, KITLG, SLC25A11, CA2,ME2, FUT4, CXCL11, IFT20, TLK1, RBM25, AK2, SFRS2, TRMT5, KLHL24, STAT1,FKBP9 303 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 77% 79% 88% 79% 81% 76%PRDX3, MTHFD2, PSME2, MCM6, TK1, DLGAP4, TYMS, TES, MAD2L1, CDC40,CXCL9, CXCL10, FAS, PLK4, CHEK1, TRIM25, C1QBP, NDUFA9, WHSC1, CA2, ME2,CXCL11, GZMB, RBBP4, SLC4A4, RBM25, CAMSAP1L1, DDAH2, AGPAT5, MARCH5,SEC10L1, PBK, BRIP1, TRMT5, ETNK1, STAT1, CHAF1A, ITGB5, HNRPDL 304HNRPD, WARS, SFRS2, MTHFD2, PSME2, 81% 79% 81% 83% 81% 72% TK1, GMFB,DLGAP4, TYMS, LMAN1, DCK, MAD2L1, CXCL9, CXCL10, FAS, KITLG, KPNB1,SLC25A11, WHSC1, ME2, CXCL11, IFT20, SLC4A4, RBM25, BRRN1, ATP5A1,CDC42BPA, BAZ1A, MARCH5, SEC10L1, PBK, PSAT1, BRIP1, KLHL24, STAT1,RBM28 305 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 77% 83% 77% 83% 88% 79%PSME2, GMFB, DLGAP4, TYMS, USP4, CDC40, CXCL9, CXCL10, PLK4, HNRPA3P1,TRIM25, SLC25A11, KPNB1, ME2, SLC4A4, RBM25, hCAP-D3, FAS, RBBP4, BAZ1A,DKFZp762E1312, SEC10L1, KLHL24, STAT1, PSME1, BUB3, SOCS6 306 WARS,EPAS1, STAT1, EIF4E, MTHFD2, 73% 79% 85% 79% 81% 76% PSME2, GMFB,DLGAP4, TYMS, USP4, TES, CTSS, ARF6, SLC4A4, CXCL9, RABIF, CXCL10, FAS,PLK4, KITLG, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, CA2, HNRPD, ME2,FUT4, CXCL11, IFT20, RBM25, CAMSAP1L1, SOCS6, DDAH2, AGPAT5, FLJ10534,MARCH5, SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, ETNK1, RPS2, CHAF1A,LGALS3BP 307 WARS, SFRS2, MTHFD2, PSME2, GMFB, 85% 93% 85% 83% 81% 83%DLGAP4, TYMS, CXCL9, GTSE1, RABIF, CXCL10, HNRPA3P1, TRIM25, KITLG,C1QBP, NDUFA9, WHSC1, CA2, ME2, FUT4, RBM25, hCAP-D3, ATP5A1, DDAH2,FAS, STAT1, CDCA8, HMGB3 308 WARS, MTHFD2, PSME2, GBP1, 81% 76% 81% 83%77% 69% MAD2L1, CXCL9, IRF8, CXCL10, CHEK1, KITLG, ME2, CXCL11, IFT20,RBM25, AK2, ATP5A1, FAS, AGPAT5, SEC10L1, FLJ13220, HNRPD, KLHL24,ETNK1, STAT1, ECGF1 309 WARS, SFRS2, EPAS1, EIF4E, PRDX3, 81% 83% 88%76% 73% 76% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, TES, CDC40, SLC4A4,CXCL9, GTSE1, CXCL10, FAS, PLK4, CHEK1, KITLG, C1QBP, NDUFA9, SLC25A11,WHSC1, C17orf25, ME2, FUT4, CXCL11, IFT20, RBBP4, RBM25, AK2, NUP210,BRRN1, CDC42BPA, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK,TRMT5, ETNK1, STAT1, SELL, GART 310 WARS, SFRS2, EPAS1, STAT1, EIF4E,73% 72% 85% 83% 69% 72% SFPQ, MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS,USP4, CTSS, ARF6, CDC40, CXCL9, GTSE1, CXCL10, FAS, PLK4, CHEK1, TRIM25,SLC25A11, C1QBP, NDUFA9, WHSC1, ME2, FUT4, CXCL11, IFT20, RBBP4, SLC4A4,RBM25, hCAP-D3, DDAH2, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220,PSAT1, HNRPD, BRIP1, KLHL24, ETNK1, WFDC1, YTHDF3, K-ALPHA-1, PAWR 311HNRPD, WARS, SFRS2, STAT1, EIF4E, 81% 83% 88% 83% 73% 79% PRDX3, MTHFD2,PSME2, TK1, GMFB, DLGAP4, TYMS, TES, LMAN1, MAD2L1, CDC40, CXCL9, IRF8,CXCL10, PLK4, HNRPA3P1, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2,FUT4, CXCL11, IFT20, RBM25, BRRN1, CDC42BPA, FAS, AGPAT5, DKFZp762E1312,SEC10L1, FLJ13220, PBK, BRIP1, KLHL24, SMC2L1, IRF1 312 WARS, EPAS1,STAT1, MTHFD2, PSME2, 73% 79% 81% 79% 77% 76% MCM6, GMFB, DLGAP4, TYMS,USP4, CTSS, LMAN1, CXCL9, IRF8, CXCL10, KITLG, C1QBP, NDUFA9, SLC25A11,ME2, SLC4A4, RBM25, hCAP-D3, SOCS6, FAS, RBBP4, BAZ1A, AGPAT5, PSAT1,BRIP1, ETNK1, LPP, PPM1D, LAP3, TXNDC 313 WARS, EIF4E, PRDX3, PSME2,TK1, 77% 76% 85% 79% 77% 83% GMFB, DLGAP4, TYMS, LMAN1, CXCL10,SLC25A11, C1QBP, NDUFA9, KPNB1, C17orf25, CA2, ME2, RBBP4, SLC4A4,RBM25, FAS, SEC10L1, PBK, HNRPD, ETNK1, STAT1, KIAA0828, SPCS3, NARS 314HNRPD, WARS, SFRS2, EPAS1, EIF4E, 81% 76% 85% 79% 81% 79% SFPQ, PRDX3,MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, CDC40,SLC4A4, CXCL9, IRF8, CXCL10, FAS, PLK4, KITLG, C1QBP, NDUFA9, SLC25A11,WHSC1, CA2, ME2, GZMB, CXCL11, RBM25, CAMSAP1L1, CDC42BPA, FLJ10534,MARCH5, FLJ13220, PBK, PSAT1, BRIP1, KLHL24, STAT1, NUP160, HLA-E 315WARS, EIF4E, SFPQ, PRDX3, MTHFD2, 73% 79% 85% 83% 77% 72% MCM6, GMFB,DLGAP4, TYMS, CDC40, CXCL9, CXCL10, CHEK1, HNRPA3P1, C1QBP, SLC25A11,WHSC1, CA2, ME2, CXCL11, SLC4A4, RBM25, AK2, SFRS2, FAS, MARCH5,FLJ13220, KLHL24, ETNK1, STAT1, SOCS1 316 WARS, EIF4E, MTHFD2, PSME2,GMFB, 81% 83% 81% 79% 85% 76% DLGAP4, USP4, DCK, CDC40, CXCL9, CXCL10,FAS, SLC25A11, C1QBP, KPNB1, WHSC1, CA2, ME2, FUT4, CXCL11, RBM25,DDAH2, SEC10L1, PBK, HNRPD, TRMT5, KLHL24, STAT1, PPA2, GTSE1,TNFRSF11A, RYK 317 WARS, SFRS2, EPAS1, PSME2, TK1, 77% 90% 85% 79% 85%83% GMFB, DLGAP4, TYMS, CTSS, LMAN1, CDC40, SLC4A4, CXCL9, IRF8, CXCL10,PLK4, CHEK1, SLC25A11, C1QBP, KPNB1, WHSC1, CA2, ME2, GZMB, TLK1,CXCL11, RBM25, hCAP-D3, FAS, RBBP4, FLJ10534, MARCH5, HNRPD, STAT1,KIF2C, HAT1 318 WARS, EIF4E, PRDX3, PSME2, GBP1, 69% 83% 77% 86% 81% 83%TYMS, LMAN1, CXCL9, CXCL10, FAS, CHEK1, SLC25A11, NDUFA9, CA2, ME2,RBBP4, TLK1, CXCL11, SLC4A4, BRRN1, PBK, HNRPD, STAT1, TGFB2 319 WARS,SFRS2, EPAS1, EIF4E, SFPQ, 92% 90% 88% 79% 73% 79% PRDX3, MTHFD2, PSME2,TK1, DLGAP4, TYMS, LMAN1, SLC4A4, CXCL9, CXCL10, PLK4, SLC25A11, WHSC1,C17orf25, CA2, ME2, CXCL11, GZMB, IFT20, RBM25, NUP210, CAMSAP1L1,ATP5A1, FAS, RBBP4, AGPAT5, FLJ10534, PBK, PSAT1, HNRPD, STAT1, HLA-DMB320 SFRS2, EIF4E, PRDX3, MTHFD2, PSME2, 73% 86% 73% 76% 81% 79% DLGAP4,TYMS, CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, TRIM25, SLC25A11, C1QBP,NDUFA9, CA2, ME2, CXCL11, SLC4A4, RBM25, ATP5A1, FLJ13220, PSAT1, BRIP1,STAT1, RIF1, SCC-112, U2AF2 321 HNRPD, WARS, STAT1, EIF4E, SFPQ, 77% 83%81% 79% 81% 76% PRDX3, MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS,CTSS, LMAN1, DCK, CDC40, SLC4A4, CXCL9, CXCL10, FAS, PLK4, TRIM25,SLC25A11, NUUFA9, WHSC1, C17orf25, CA2, ME2, FUT4, CXCL11, IFT20, RBM25,AK2, BRRN1, SFRS2, DDAH2, MARCH5, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,KLHL24, CD8A, GTF2H2, C14orf156, BIRC5 322 HNRPD, WARS, SFRS2, EPAS1,STAT1, 77% 79% 81% 83% 88% 76% EIF4E, SFPQ, PRDX3, MTHFD2, PSME2, MCM6,TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, CXCL9, RABIF, CXCL10, FAS,TRIM25, NDUFA9, KPNB1, WHSC1, CA2, ME2, RBBP4, SLC4A4, RBM25, NUP210,hCAP-D3, SOCS6, BAZ1A, PBK, PSAT1, BRIP1, KLHL24, MAX, HADHSC 323 WARS,SFRS2, EIF4E, MTHFD2, PSME2, 88% 83% 88% 76% 85% 79% TK1, GMFB, DLGAP4,TYMS, TES, CTSS, ARF6, MAD2L1, CDC40, CXCL9, IRF8, CXCL10, TRIM25,SLC25A11, C1QBP, NDUFA9, CA2, ME2, CXCL11, GZMB, SLC4A4, RBM25, AK2,NUP210, BRRN1, ATP5A1, DDAH2, FAS, MARCH5, SEC10L1, PBK, HNRPD, ETNK1,STAT1, AP1G1 324 WARS, STAT1, PRDX3, MTHFD2, PSME2, 73% 76% 81% 83% 85%86% TK1, GMFB, DLGAP4, TYMS, CTSS, LMAN1, ARF6, MAD2L1, CDC40, CXCL9,CXCL10, FAS, PLK4, TRIM25, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1,CA2, HNRPD, ME2, FUT4, CXCL11, RBM25, CAMSAP1L1, hCAP-D3, BRRN1, ATP5A1,SOCS6, RBBP4, SEC10L1, PBK, BRIP1, KLHL24, ETNK1, MIS12, RBMS3, RUNX1,TTC19 325 HNRPD, WARS, SFRS2, EIF4E, MTHFD2, 85% 76% 92% 76% 85% 76%PSME2, GMFB, DLGAP4, TYMS, MAD2L1, CXCL10, FAS, HNRPA3P1, NDUFA9,SLC25A11, CA2, ME2, GZMB, CXCL11, hCAP-D3, RBBP4, BAZ1A, AGPAT5,FLJ10534, ETNK1, STAT1, JAK2, RNGTT 326 WARS, PAICS, EIF4E, SFPQ,MTHFD2, 73% 76% 81% 79% 77% 66% PSME2, GMFB, DLGAP4, TYMS, USP4, TES,ARF6, CDC40, CXCL9, RABIF, CXCL10, FAS, TRIM25, KITLG, C1QBP, NDUFA9,SLC25A11, WHSC1, ME2, FUT4, CXCL11, SLC4A4, RBM25, CAMSAP1L1, hCAP-D3,CDC42BPA, AGPAT5, PBK, PSAT1, HNRPD, BRIP1, STAT1, CDC2, ATP13A3,ZC3HAV1, FANCA 327 WARS, EIF4E, MTHFD2, PSME2, TK1, 77% 79% 85% 79% 69%79% GMFB, TYMS, CXCL9, CXCL10, FAS, SLC25A11, WHSC1, C17orf25, CA2, ME2,RBM25, NUP210, BAZ1A, FLJ10534, MARCH5, SEC10L1, HNRPD, BRIP1, KLHL24,ETNK1, STAT1, SGPP1, CLCA4, FOXM1 328 HNRPD, WARS, SFRS2, EPAS1, STAT1,88% 83% 85% 79% 81% 76% EIF4E, MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4,TYMS, TES, LMAN1, DCK, ARF6, CDC40, CXCL9, CXCL10, FAS, PLK4, TRIM25,KITLG, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2, TLK1,CXCL11, SLC4A4, RBM25, AK2, hCAP-D3, BAZ1A, AGPAT5, SEC10L1, FLJ13220,PBK, KLHL24, ETNK1, MCAM, BUB3, YTHDC2, APOL6, NUP210 329 WARS, SFRS2,EPAS1, EIF4E, MTHFD2, 88% 86% 85% 76% 77% 72% PSME2, MCM6, TK1, GMFB,DLGAP4, TYMS, USP4, TES, LMAN1, ARF6, CDC40, CXCL9, IRF8, GTSE1, RABIF,CXCL10, FAS, HNRPA3P1, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, C17orf25,CA2, HNRPD, ME2, CXCL11, GZMB, SLC4A4, RBM25, AK2, SOCS6, CDC42BPA,RBBP4, AGPAT5, MARCH5, SEC10L1, PSAT1, BRIP1, KLHL24, ETNK1, STAT1,CACNB3, BUB1B, ESPL1, H2AFZ 330 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 77%79% 73% 79% 65% 69% PSME2, TK1, GMFB, DLGAP4, USP4, CXCL9, CXCL10,NDUFA9, KPNB1, SLC25A11, C17orf25, ME2, CXCL11, RBBP4, hCAP-D3, ATP5A1,FAS, AGPAT5, FLJ10534, PBK, PSAT1, HNRPD, BRIP1, ETNK1, STAT1, LHCGR 331WARS, EIF4E, MTHFD2, PSME2, GBP1, 69% 72% 73% 86% 81% 76% DLGAP4, TYMS,CTSS, CDC40, SLC4A4, IRF8, CXCL10, FAS, TRIM25, SLC25A11, C1QBP, NDUFA9,ME2, FUT4, RBBP4, TLK1, RBM25, AK2, FLJ10534, MARCH5, FLJ13220, ETNK1,STAT1, C18orf9, C10orf3, AURKB, IFI16, PTPRC 332 HNRPD, WARS, PAICS,EIF4E, PRDX3, 77% 83% 88% 76% 77% 72% MTHFD2, TK1, GMFB, TYMS, CTSS,CXCL9, FAS, KITLG, NDUFA9, SLC25A11, C17orf25, ME2, FUT4, CXCL11, IFT20,SLC4A4, RBM25, CDC42BPA, SFRS2, AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK,PSAT1, BRIP1, KLHL24, STAT1, AK2 333 WARS, EIF4E, PRDX3, MTHFD2, PSME2,88% 86% 85% 66% 65% 79% MCM6, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1,CXCL9, CXCL10, FAS, PLK4, HNRPA3P1, TRIM25, SLC25A11, WHSC1, ME2,CXCL11, IFT20, SLC4A4, RBM25, BAZ1A, AGPAT5, DKFZp762E1312, SEC10L1,PBK, HNRPD, BRIP1, ETNK1, STAT1, TOP2A, NUSAP1, USP14, PRF1, SCYL2 334WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 88% 93% 88% 86% 73% 83% PSME2, GMFB,DLGAP4, TYMS, USP4, CXCL10, FAS, WHSC1, C17orf25, ME2, IFT20, TLK1,CXCL11, SLC4A4, RBM25, AK2, CDC42BPA, HNRPD, ETNK1, STAT1, HLA-DRA,POLE2, PAICS, NUP210 335 HNRPD, WARS, EIF4E, PRDX3, MTHFD2, 81% 83% 92%79% 88% 83% PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, CDC40,CXCL9, PLK4, SLC25A11, WHSC1, C17orf25, CA2, ME2, IFT20, CXCL11, RBM25,hCAP-D3, FAS, FLJ10534, DKFZp762E1312, SEC10L1, ETNK1, STAT1, WDHD1 336WARS, SFRS2, EPAS1, EIF4E, PRDX3, 77% 86% 85% 76% 81% 76% MTHFD2, PSME2,MCM6, GBP1, GMFB, DLGAP4, TYMS, USP4, CTSS, MAD2L1, CXCL9, IRF8, GTSE1,CXCL10, FAS, CHEK1, KITLG, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25,CA2, ME2, CXCL11, GZMB, IFT20, TLK1, SLC4A4, RBM25, hCAP-D3, BAZ1A,MARCH5, DKFZp762E1312, SEC10L1, FLJ13220, PSAT1, HNRPD, BRIP1, KLHL24,ETNK1, STAT1, CUTL1, FAM64A 337 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 77%79% 92% 69% 92% 79% PSME2, GMFB, DLGAP4, TYMS, CTSS, LMAN1, CDC40,CXCL9, IRF8, SLC25A11, C1QBP, NDUFA9, CA2, ME2, FUT4, CXCL11, RBM25,AK2, CDC42BPA, FAS, RBBP4, AGPAT5, MARCH5, SEC10L1, PBK, HNRPD, BRIP1,TRMT5, STAT1, TMEPAI, ZNF304, KLF7 338 WARS, SFRS2, EPAS1, STAT1, EIF4E,81% 93% 92% 79% 81% 72% SFPQ, PRDX3, MTHFD2, PSME2, GBP1, GMFB, DLGAP4,TYMS, CDC40, SLC4A4, CXCL9, RABIF, CXCL10, FAS, CHEK1, TRIM25, SLC25A11,C1QBP, NDUFA9, WHSC1, CA2, HNRPD, ME2, GZMB, RBBP4, CXCL11, RBM25, AK2,NUP210, BRRN1, ATP5A1, CDC42BPA, AGPAT5, FLJ10534, MARCH5, SEC10L1,FLJ13220, PBK, PSAT1, BRIP1, MCM10, HLA-DMA, RABEP1, YARS, P15RS 339WARS, STAT1, EIF4E, MTHFD2, PSME2, 73% 79% 77% 79% 69% 83% GMFB, DLGAP4,MAD2L1, FAS, PLK4, TRIM25, KITLG, SLC25A11, KPNB1, WHSC1, ME2, CXCL11,SLC4A4, RBM25, AK2, AGPAT5, KLHL24, CDKN1C, RFC5, FEN1, TFRC 340 WARS,EIF4E, MTHFD2, PSME2, TK1, 73% 79% 85% 83% 81% 72% GMFB, DLGAP4, TYMS,TES, LMAN1, DCK, CDC40, CXCL9, IRF8, GTSE1, CXCL10, FAS, PLK4, TRIM25,SLC25A11, C1QBP, NDUFA9, C17orf25, CA2, ME2, FUT4, CXCL11, SLC4A4,RBM25, AK2, CDC42BPA, RBBP4, BAZ1A, AGPAT5, FLJ10534, SEC10L1, FLJ13220,PBK, PSAT1, HNRPD, KLHL24, ETNK1, STAT1, SPFH1, SP3, CDC20, RAP1GDS1,M11S1 341 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 96% 90% 81% 72% 73% 72%PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, ARF6, SLC4A4, CXCL9,CXCL10, FAS, TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25,HNRPD, ME2, GZMB, TLK1, CXCL11, RBM25, AK2, BRRN1, DDAH2, AGPAT5,FLJ10534, SEC10L1, FLJ13220, PBK, PSAT1, TRMT5, KLHL24, ETNK1, STAT1,AVEN, HLA-DPA1, CD59 342 WARS, SFRS2, EPAS1, PRDX3, MTHFD2, 81% 83% 92%79% 85% 79% TK1, GMFB, DLGAP4, TYMS, TES, LMAN1, SLC4A4, GTSE1, CXCL10,FAS, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2,FUT4, CXCL11, R8M25, CDC42BPA, RBBP4, BAZ1A, AGPAT5, MARCH5, SEC10L1,BRIP1, TRMT5, KLHL24, STAT1, MPP5, EIF4A1, TRIP13, APOL3 343 WARS,SFRS2, EIF4E, PRDX3, MTHFD2, 69% 79% 85% 83% 88% 76% PSME2, TK1, GMFB,DLGAP4, TYMS, LMAN1, CDC40, CXCL9, CXCL10, FAS, CHEK1, HNRPA3P1,SLC25A11, C1QBP, WHSC1, CA2, HNRPD, ME2, CXCL11, TLK1, SLC4A4, RBM25,AK2, ATP5A1, SOCS6, BAZ1A, AGPAT5, MARCH5, DKFZp762E1312, SEC10L1, PBK,BRIP1, KLHL24, STAT1, GPR161, SGCD 344 WARS, SFRS2, EIF4E, PRDX3, PSME2,77% 86% 92% 79% 88% 86% GMFB, DLGAP4, TYMS, USP4, MAD2L1, CDC40, SLC4A4,CXCL10, FAS, CHEK1, KITLG, NDUFA9, KPNB1, SLC25A11, CA2, HNRPD, ME2,FUT4, GZMB, CXCL11, RBM25, BRRN1, CDC42BPA, MARCH5, KLHL24, ETNK1,STAT1, ADH1C, WHSC1, HIP2 345 WARS, SFRS2, EPAS1, PAICS, EIF4E, 81% 86%88% 83% 88% 72% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, USP4, DCK, ARF6,SLC4A4, CXCL9, RABIF, CXCL10, FAS, TRIM25, SLC25A11, C1QBP, NDUFA9,WHSC1, C17orf25, CA2, HNRPD, ME2, FUT4, GZMB, IFT20, CXCL11, RBM25, AK2,CAMSAP1L1, BRRN1, DDAH2, RBBP4, AGPAT5, PBK, PSAT1, BRIP1, KLHL24,STAT1, XPO7, TRAFD1, YTHDC2, RNF138 346 WARS, SFRS2, EPAS1, PRDX3,MTHFD2, 81% 83% 85% 76% 81% 72% PSME2, MCM6, DLGAP4, TYMS, USP4, CDC40,SLC4A4, CXCL9, RABIF, CXCL10, FAS, SLC25A11, C1QBP, NDUFA9, WHSC1, CA2,ME2, CXCL11, RBM25, NUP210, BRRN1, DDAH2, RBBP4, BAZ1A, DKFZp762E1312,SEC10L1, PSAT1, HNRPD, KLHL24, ETNK1, STAT1, ACADSB, AMIGO2, CCL5,KIAA0286 347 SFRS2, EPAS1, EIF4E, SFPQ, PRDX3, 81% 83% 92% 79% 85% 79%MTHFD2, PSME2, GMFB, DLGAP4, TYMS, LMAN1, DCK, ARF6, CDC40, CXCL9,GTSE1, CXCL10, FAS, SLC25A11, KPNB1, WHSC1, CA2, HNRPD, ME2, CXCL11,SLC4A4, RBM25, AK2, ATP5A1, CDC42BPA, BAZ1A, FLJ10534, FLJ13220, PBK,BRIP1, KLHL24, STAT1, PSMB9, HBP1, CPD, AIM2 348 WARS, EPAS1, EIF4E,PRDX3, MTHFD2, 73% 86% 73% 86% 73% 79% MCM6, GMFB, DLGAP4, CDC40,CXCL10, CHEK1, KPNB1, CA2, ME2, RBBP4, CXCL11, SLC4A4, RBM25, CDC42BPA,FAS, FLJ10534, SEC10L1, FLJ13220, HNRPD, STAT1, TTK, YBX2, BCL7C, SI 349WARS, SFRS2, STAT1, EIF4E, PRDX3, 88% 79% 96% 69% 88% 76% MTHFD2, TK1,GMFB, DLGAP4, TYMS, USP4, TES, CTSS, CXCL9, CXCL10, FAS, SLC25A11,KPNB1, C17orf25, ME2, GZMB, SLC4A4, NUP210, hCAP-D3, HNRPD, TRMT5,KLHL24, PRO2730 350 EPAS1, EIF4E, PRDX3, PSME2, GMFB, 73% 83% 92% 79%81% 76% DLGAP4, TYMS, USP4, CTSS, SLC4A4, CXCL10, HNRPA3P1, KITLG,SLC25A11, WHSC1, CA2, HNRPD, ME2, FUT4, RBM25, CAMSAP1L1, FAS, AGPAT5,FLJ10534, MARCH5, SEC10L1, PSAT1, BRIP1, KLHL24, STAT1, MCM2, GGA2,SPAG5, VRK1, EBNA1BP2 351 WARS, SFRS2, EIF4E, MTHFD2, PSME2, 85% 76% 88%83% 88% 76% TK1, GMFB, DLGAP4, TYMS, LMAN1, MAD2L1, SLC4A4, CXCL9,RABIF, CXCL10, FAS, CHEK1, KITLG, SLC25A11, NDUFA9, C17orf25, CA2, ME2,IFT20, CXCL11, RBM25, hCAP-D3, CDC42BPA, AGPAT5, MARCH5, HNRPD, KLHL24,STAT1, MYCBP, GBP1, ITGA4, PBXIP1, CENPA 352 HNRPD, WARS, SFRS2, EPAS1,EIF4E, 77% 79% 92% 76% 77% 76% PRDX3, MTHFD2, PSME2, GMFB, DLGAP4, TYMS,TES, CTSS, ARF6, CDC40, SLC4A4, CXCL9, CXCL10, FAS, TRIM25, KITLG,NDUFA9, SLC25A11, C17orf25, CA2, ME2, FUT4, GZMB, CXCL11, BRRN1, SOCS6,CDC42BPA, BAZ1A, DKFZp762E1312, SEC10L1, PBK, PSAT1, BRIP1, TRMT5,ETNK1, STAT1, PPIG, NUP98, FUSIP1, SH3GLB1 353 WARS, SFRS2, EPAS1,EIF4E, PRDX3, 85% 83% 88% 79% 73% 72% MTHFD2, PSME2, GMFB, DLGAP4, TYMS,DCK, CDC40, CXCL9, GTSE1, RABIF, CXCL10, KITLG, C1QBP, NDUFA9, SLC25A11,C17orf25, CA2, ME2, GZMB, IFT20, SLC4A4, RBM25, DDAH2, FAS, AGPAT5,FLJ10534, MARCH5, FLJ13220, PBK, HNRPD, KLHL24, ETNK1, STAT1, C5orf4,KIF23, SSPN 354 HNRPD, WARS, SFRS2, STAT1, EIF4E, 85% 83% 92% 83% 81%76% SFPQ, PSME2, GBP1, GMFB, DLGAP4, TYMS, CTSS, ARF6, CDC40, SLC4A4,CXCL10, FAS, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, IFT20, RBBP4,CXCL11, RBM25, NUP210, BAZ1A, AGPAT5, MARCH5, PBK, KLHL24, MAP2K4,UBE2L6 355 HNRPD, WARS, EIF4E, MTHFD2, MCM6, 88% 90% 73% 79% 73% 76%DLGAP4, TYMS, CDC40, CXCL9, CXCL10, FAS, TRIM25, C1QBP, ME2, CXCL11,RBM25, AK2, CDC42BPA, SEC10L1, PBK, KLHL24, ETNK1, STAT1, DNA2L, TAP2,SYNPO 356 HNRPD, WARS, EIF4E, MTHFD2, GBP1, 69% 83% 85% 83% 81% 79%GMFB, DLGAP4, TYMS, USP4, DCK, CDC40, CXCL9, IRF8, GTSE1, CXCL10,HNRPA3P1, TRIM25, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2, ME2, FUT4,CXCL11, RBBP4, TLK1, SLC4A4, RBM25, AK2, NUP210, ATP5A1, SFRS2, FAS,AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, KLHL24, ETNK1, STAT1, EXOSC9,KIF15, FBXL14, ABCE1 357 WARS, EPAS1, EIF4E, PRDX3, MTHFD2, 85% 86% 88%79% 81% 72% PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, TES, CTSS, LMAN1,CDC40, SLC4A4, CXCL9, IRF8, CXCL10, FAS, PLK4, HNRPA3P1, C1QBP, NDUFA9,SLC25A11, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, RBM25, AK2,CDC42BPA, RBBP4, AGPAT5, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1, STAT1,CCL5, FLJ20516, BUB1, MRPL42 358 HNRPD, WARS, EIF4E, MTHFD2, PSME2, 77%83% 85% 79% 81% 69% GBP1, GMFB, DLGAP4, TYMS, USP4, ARF6, MAD2L1, CDC40,SLC4A4, CXCL9, CXCL10, FAS, PLK4, C1QBP, SLC25A11, WHSC1, CA2, ME2,CXCL11, RBBP4, RBM25, AK2, CDC42BPA, BAZ1A, AGPAT5, SEC10L1, PBK, PSAT1,BRIP1, ETNK1, STAT1, GZMA, EIF4A1, PSMA3, CD2, CCNB1 359 WARS, PSME2,GMFB, DLGAP4, TYMS, 77% 79% 81% 76% 77% 66% CDC40, CXCL9, GTSE1, CXCL10,FAS, TRIM25, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, ME2, CXCL11,RBM25, CAMSAP1L1, AGPAT5, FLJ13220, PSAT1, TRMT5, KLHL24, ETNK1, STAT1,RRM1, CXCL13, NKG7, MGAT2, LCP2 360 HNRPD, SFRS2, EPAS1, STAT1, EIF4E,88% 90% 85% 79% 73% 76% MTHFD2, PSME2, TK1, GMFB, DLGAP4, TYMS, CXCL9,CXCL10, FAS, CHEK1, HNRPA3P1, KPNB1, SLC25A11, WHSC1, C17orf25, ME2,CXCL11, IFT20, TLK1, SLC4A4, RBM25, CDC42BPA, BAZ1A, AGPAT5, MARCH5,SEC10L1, PBK, PSAT1, KLHL24, C1orf112, TCF7L2, RARRES3, SERBP1, TBX2 361HNRPD, WARS, EIF4E, SFPQ, MTHFD2, 81% 83% 88% 76% 77% 69% PSME2, GMFB,DLGAP4, TYMS, TES, CTSS, ARF6, CXCL9, IRF8, RABIF, CXCL10, FAS, PLK4,HNRPA3P1, KITLG, SLC25A11, C1QBP, NDUFA9, WHSC1, C17orf25, ME2, CXCL11,IFT20, TLK1, RBM25, AK2, NUP210, hCAP-D3, CDC42BPA, DDAH2, AGPAT5,FLJ10534, SEC10L1, PBK, KLHL24, STAT1, PTGER3, HCAP-G 362 HNRPD, WARS,SFRS2, EPAS1, STAT1, 81% 90% 85% 79% 77% 83% EIF4E, SFPQ, PRDX3, MTHFD2,PSME2, TK1, GMFB, DLGAP4, TYMS, CTSS, LMAN1, MAD2L1, CDC40, CXCL9, IRF8,CXCL10, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2, CXCL11, GZMB, IFT20,RBBP4, SLC4A4, RBM25, hCAP-D3, BRRN1, FAS, FLJ10534, SEC10L1, PSAT1,KLHL24, NUP50, MCCC2, RABGEF1 363 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 92%90% 77% 83% 69% 72% GMFB, DLGAP4, TYMS, USP4, CDC40, CXCL9, CXCL10, FAS,HNRPA3P1, TRIM25, C1QBP, SLC25A11, ME2, CXCL11, IFT20, RBM25, AK2,hCAP-D3, CDC42BPA, RBBP4, BAZ1A, DKFZp762E1312, SEC10L1, PBK, HNRPD,ETNK1, STAT1, PSMA6, ZNF345, UBAP1 364 WARS, EPAS1, PAICS, EIF4E,MTHFD2, 77% 86% 88% 76% 85% 76% PSME2, GMFB, TYMS, TES, LMAN1, SLC4A4,CXCL9, RABIF, FAS, CHEK1, HNRPA3P1, TRIM25, SLC25A11, C1QBP, WHSC1, ME2,CDC42BPA, FLJ10534, SEC10L1, PBK, STAT1, ZBTB20, NAT2 365 WARS, SFRS2,EIF4E, MTHFD2, PSME2, 85% 86% 85% 76% 81% 69% GMFB, DLGAP4, TYMS, USP4,MAD2L1, CXCL9, CXCL10, FAS, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, CA2,ME2, IFT20, SLC4A4, RBM25, AK2, CDC42BPA, DDAH2, PSAT1, HNRPD, BRIP1,KLHL24, ETNK1, STAT1, HMMR, CTSL 366 WARS, EIF4E, PRDX3, MTHFD2, PSME2,88% 83% 85% 72% 69% 76% GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, CXCL9,CXCL10, FAS, TRIM25, WHSC1, C17orf25, CA2, ME2, FUT4, IFT20, CXCL11,SLC4A4, RBM25, CDC42BPA, RBBP4, AGPAT5, MARCH5, FLJ13220, PBK, HNRPD,TRMT5, KLHL24, ETNK1, STAT1, PBX1, ZDHHC3, CLEC2D 367 HNRPD, WARS,SFRS2, EIF4E, MTHFD2, 73% 83% 85% 83% 73% 66% PSME2, TK1, GMFB, DLGAP4,TYMS, TES, LMAN1, ARF6, CDC40, CXCL9, IRF8, GTSE1, RABIF, CXCL10, FAS,KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2, TLK1, SLC4A4, CXCL11, RBM25,hCAP-D3, DDAH2, RBBP4, BAZ1A, AGPAT5, SEC10L1, PBK, TRMT5, KLHL24,ETNK1, STAT1, NEK2, KIAA0841, RNMT, C4orf16 368 WARS, SFRS2, EPAS1,STAT1, MTHFD2, 73% 83% 81% 79% 81% 72% PSME2, GMFB, DLGAP4, TYMS, TES,CDC40, SLC4A4, CXCL9, RABIF, CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, TRIM25,C1QBP, KPNB1, SLC25A11, WHSC1, CA2, HNRPD, ME2, FUT4, RBBP4, CXCL11,RBM25, NUP210, SOCS6, CDC42BPA, FLJ10534, MARCH5, FLJ13220, PBK, PSAT1,BRIP1, KLHL24, APOL1, PDGFA, FBXO5, CACYBP, ABCE1 369 WARS, SFRS2,EPAS1, STAT1, PAICS, 88% 86% 81% 83% 81% 79% EIF4E, MTHFD2, PSME2, GMFB,DLGAP4, TYMS, USP4, DCK, CDC40, SLC4A4, CXCL9, GTSE1, CXCL10, PLK4,SLC25A11, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2, FUT4, IFT20, TLK1,CXCL11, RBM25, AK2, CDC42BPA, DDAH2, FAS, BAZ1A, AGPAT5, SEC10L1,FLJ13220, PBK, PSAT1, HNRPD, BRIP1, BMP5, ETNK1, PTGER3, VAMP4, CCNB2370 WARS, EPAS1, PRDX3, MTHFD2, PSME2, 81% 79% 81% 79% 81% 76% TK1,GMFB, DLGAP4, TYMS, TES, CTSS, MAD2L1, CDC40, SLC4A4, CXCL9, GTSE1,RABIF, CXCL10, FAS, PLK4, TRIM25, KITLG, SLC25A11, C1QBP, CA2, ME2,CXCL11, RBBP4, TLK1, RBM25, AK2, BRRN1, SFRS2, BAZ1A, AGPAT5, FLJ13220,PSAT1, HNRPD, BRIP1, KLHL24, STAT1, TAP1, LCP2, ITGAL, CCNT2, FYB 371HNRPD, WARS, PRDX3, MTHFD2, 88% 79% 85% 79% 73% 72% PSME2, MCM6, TK1,GMFB, DLGAP4, TYMS, DCK, ARF6, CXCL9, CXCL10, C1QBP, NDUFA9, SLC25A11,ME2, IFT20, CXCL11, RBM25, AK2, BRRN1, ATP5A1, CDC42BPA, SFRS2, FAS,BAZ1A, AGPAT5, FLJ13220, PBK, PSAT1, BRIP1, KLHL24, STAT1, NEIL3,PCDHGC3, NUSAP1 372 SFRS2, EPAS1, EIF4E, PRDX3, MTHFD2, 77% 79% 81% 83%85% 79% PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, TES, DCK, MAD2L1, CXCL9,IRF8, CXCL10, FAS, TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, CA2,HNRPD, ME2, CXCL11, IFT20, RBBP4, SLC4A4, RBM25, AK2, CDC42BPA, DDAH2,BAZ1A, AGPAT5, FLJ10534, MARCH5, SEC10L1, FLJ13220, PBK, KLHL24, ETNK1,STAT1, TNFAIP2 373 WARS, STAT1, EIF4E, SFPQ, MTHFD2, 85% 86% 92% 79% 81%72% PSME2, GMFB, DLGAP4, TYMS, ARF6, CDC40, SLC4A4, CXCL9, RABIF,CXCL10, FAS, SLC25A11, C1QBP, NDUFA9, KPNB1, WHSC1, C17orf25, CA2, ME2,FUT4, CXCL11, GZMB, TLK1, RBM25, AK2, FLJ10534, FLJ13220, HNRPD, BRIP1,GEMIN4, PTPRC 374 WARS, SFRS2, EPAS1, PAICS, EIF4E, 77% 90% 81% 76% 85%76% MTHFD2, PSME2, MCM6, GBP1, GMFB, DLGAP4, TYMS, TES, CTSS, DCK,MAD2L1, CDC40, SLC4A4, CXCL9, IRF8, GTSE1, CXCL10, FAS, PLK4, TRIM25,KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1, CA2, ME2, CXCL11, RBM25,AK2, hCAP-D3, CDC42BPA, DDAH2, AGPAT5, MARCH5, SEC10L1, FLJ13220, PBK,HNRPD, BRIP1, KLHL24, STAT1, APOBEC3G, KIF11, GBP2, RAB6A, ITGB5 375WARS, EIF4E, MTHFD2, PSME2, MCM6, 73% 72% 85% 90% 81% 83% GMFB, DLGAP4,TYMS, MAD2L1, CDC40, CXCL9, CXCL10, FAS, SLC25A11, C1QBP, NDUFA9, ME2,FUT4, CXCL11, RBM25, hCAP-D3, BRRN1, MARCH5, SEC10L1, FLJ13220, HNRPD,STAT1, AP2B1, KIF2, K-ALPHA-1, GPHN 376 HNRPD, WARS, SFRS2, EPAS1,PAICS, 77% 83% 77% 86% 73% 86% EIF4E, PRDX3, MTHFD2, PSME2, GBP1, TK1,GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1, CXCL9, IRF8, RABIF, CXCL10, FAS,HNRPA3P1, KITLG, SLC25A11, C1QBP, NDUFA9, WHSC1, ME2, CXCL11, TLK1,SLC4A4, RBM25, ATP5A1, RBBP4, FLJ10534, MARCH5, FLJ13220, PSAT1, BRIP1,KLHL24, STAT1, KIF18A, KIF2C, NF2, DLG7, PSMA5 377 WARS, SFRS2, EPAS1,EIF4E, MTHFD2, 81% 90% 85% 90% 88% 72% PSME2, GMFB, DLGAP4, TYMS, CDC40,CXCL9, CXCL10, FAS, PLK4, TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, HNRPD,ME2, CXCL11, IFT20, RBM25, ATP5A1, DDAH2, AGPAT5, FLJ13220, PSAT1,BRIP1, KLHL24, STAT1, SLC4A4, CD7, DNM1L, RPL39, CDKN3 378 HNRPD, WARS,SFRS2, EPAS1, STAT1, 85% 90% 85% 72% 73% 79% EIF4E, PRDX3, MTHFD2,PSME2, TK1, DLGAP4, TYMS, USP4, LMAN1, DCK, MAD2L1, CDC40, SLC4A4,CXCL9, GTSE1, RABIF, CXCL10, FAS, PLK4, CHEK1, HNRPA3P1, TRIM25, C1QBP,NDUFA9, SLC25A11, WHSC1, ME2, CXCL11, GZMB, IFT20, RBBP4, TLK1, RBM25,AK2, ATP5A1, AGPAT5, KLHL24, ETNK1, CD3Z, DHX15, MTHFD1 379 WARS, STAT1,EIF4E, MTHFD2, PSME2, 81% 83% 77% 83% 77% 79% GMFB, DLGAP4, TYMS, LMAN1,DCK, SLC4A4, CXCL9, IRF8, RABIF, CXCL10, FAS, TRIM25, NDUFA9, SLC25A11,WHSC1, HNRPD, ME2, CXCL11, TLK1, RBM25, CAMSAP1L1, CDC42BPA, RBBP4,MARCH5, SEC10L1, FLJ13220, PSAT1, BRIP1, KLHL24, ETNK1, ATF6, RRM2,KPNA2 380 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 73% 83% 81% 86% 69% 72%MTHFD2, PSME2, GBP1, TK1, DLGAP4, TYMS, LMAN1, MAD2L1, CXCL9, IRF8,CXCL10, FAS, HNRPA3P1, KITLG, NDUFA9, KPNB1, SLC25A11, ME2, CXCL11,TLK1, SLC4A4, RBM25, AK2, AGPAT5, FLJ10534, MARCH5, SEC10L1, PBK, PSAT1,BRIP1, KLHL24, STAT1, BTN3A3 381 WARS, EIF4E, PRDX3, MTHFD2, PSME2, 85%83% 92% 86% 85% 76% TK1, GMFB, DLGAP4, TYMS, USP4, TES, CDC40, CXCL9,CXCL10, FAS, KITLG, NDUFA9, SLC25A11, WHSC1, CA2, ME2, RBM25, AK2,ATP5A1, SEC10L1, PBK, HNRPD, BRIP1, KLHL24, STAT1, CHEK1, C20orf45, CKS2382 WARS, SFRS2, EPAS1, EIF4E, MTHFD2, 92% 90% 81% 79% 73% 76% PSME2,GBP1, GMFB, DLGAP4, TYMS, USP4, ARF6, MAD2L1, CXCL9, RABIF, CXCL10, FAS,PLK4, CHEK1, HNRPA3P1, KITLG, SLC25A11, WHSC1, C17orf25, ME2, FUT4,CXCL11, IFT20, SLC4A4, RBM25, ATP5A1, CDC42BPA, RBBP4, MARCH5, SEC10L1,FLJ13220, PBK, PSAT1, ETNK1, STAT1, HMGN2, SFRS10 383 WARS, EPAS1,EIF4E, PRDX3, MTHFD2, 85% 83% 88% 76% 81% 72% PSME2, GBP1, GMFB, DLGAP4,TYMS, USP4, DCK, CDC40, CXCL9, IRF8, RABIF, CXCL10, FAS, PLK4, HNRPA3P1,TRIM25, KITLG, C1QBP, NDUFA9, SLC25A11, C17orf25, CA2, HNRPD, ME2,CXCL11, RBM25, SFRS2, DDAH2, RBBP4, AGPAT5, FLJ13220, PBK, ETNK1, STAT1,TMEM48 384 WARS, SFRS2, EPAS1, EIF4E, SFPQ, 88% 90% 88% 83% 81% 76%GMFB, DLGAP4, TYMS, USP4, SLC4A4, CXCL9, RABIF, CXCL10, FAS, KPNB1, CA2,ME2, FUT4, CXCL11, RBM25, CAMSAP1L1, KLHL24, STAT1, TRAF3IP3, SOS1 385WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 85% 86% 88% 79% 73% 79% PSME2,DLGAP4, TYMS, USP4, MAD2L1, SLC4A4, CXCL9, GTSE1, RABIF, CXCL10, FAS,HNRPA3P1, TRIM25, SLC25A11, NDUFA9, WHSC1, CA2, ME2, GZMB, TLK1, CXCL11,RBM25, AK2, BRRN1, ATP5A1, DDAH2, AGPAT5, MARCH5, SEC10L1, PBK, PSAT1,HNRPD, BRIP1, KLHL24, STAT1, C16orf30 386 WARS, SFRS2, PA1CS, EIF4E,PRDX3, 69% 76% 69% 86% 81% 86% MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4,TYMS, LMAN1, CXCL9, IRF8, GTSE1, CXCL10, FAS, TRIM25, KITLG, SLC25A11,C1QBP, NDUFA9, KPNB1, WHSC1, HNRPD, ME2, CXCL11, IFT20, RBBP4, TLK1,SLC4A4, RBM25, CAMSAP1L1, ATP5A1, DDAH2, FLJ10534, MARCH5,DKFZp762E1312, SEC10L1, PBK, TRMT5, STAT1, PGD, ZNF148 387 HNRPD, WARS,EPAS1, PRDX3, 73% 86% 88% 83% 81% 83% MTHFD2, PSME2, TK1, DLGAP4, TYMS,USP4, TES, LMAN1, CXCL9, CXCL10, FAS, PLK4, TRIM25, C1QBP, SLC25A11,WHSC1, ME2, RBBP4, TLK1, SLC4A4, NUP210, SFRS2, SEC10L1, ETNK1, STAT1,SNRPC, RAC2 388 WARS, SFRS2, PAICS, EIF4E, MTHFD2, 73% 79% 73% 86% 77%83% PSME2, GMFB, DLGAP4, TYMS, TES, LMAN1, CDC40, CXCL10, NDUFA9, KPNB1,SLC25A11, ME2, CXCL11, SLC4A4, RBM25, NUP210, hCAP-D3, FAS, RBBP4,ETNK1, STAT1, DHX40, KIAA0090 389 HNRPD, WARS, SFRS2, EPAS1, STAT1, 85%86% 88% 76% 81% 83% EIF4E, MTHFD2, PSME2, GMFB, DLGAP4, TYMS, LMAN1,ARF6, CXCL10, FAS, PLK4, TRIM25, SLC25A11, C1QBP, NDUFA9, ME2, CXCL11,GZMB, TLK1, SLC4A4, RBM25, hCAP-D3, ATP5A1, CDC42BPA, DDAH2, AGPAT5,FLJ10534, MARCH5, FLJ13220, SLA 390 WARS, EPAS1, EIF4E, PRDX3, TK1, 88%86% 81% 83% 81% 86% GMFB, DLGAP4, USP4, CXCL9, CXCL10, FAS, CHEK1,KITLG, C1QBP, NDUFA9, SLC25A11, WHSC1, ME2, IFT20, RBM25, HNRPD, BRIP1,ETNK1, STAT1, MASA, SYDE1, C9orf16, ZNF518 391 WARS, SFRS2, MTHFD2,PSME2, GMFB, 85% 79% 92% 79% 88% 76% DLGAP4, TYMS, CXCL9, RABIF, CXCL10,HNRPA3P1, TRIM25, KITLG, SLC25A11, ME2, RBBP4, CXCL11, RBM25, SOCS6,FAS, AGPAT5, MARCH5, SEC10L1, HNRPD, BRIP1, STAT1, KIAA0265, CCNA2,LRP8, CNAP1 392 HNRPD, WARS, SFRS2, EIF4E, PRDX3, 85% 90% 88% 79% 85%69% MTHFD2, PSME2, GBP1, TK1, GMFB, DLGAP4, USP4, CTSS, ARF6, CXCL9,IRF8, GTSE1, CXCL10, TRIM25, C1QBP, SLC25A11, WHSC1, CA2, ME2, FUT4,CXCL11, GZMB, SLC4A4, RBM25, AK2, CAMSAP1L1, ATP5A1, SOCS6, CDC42BPA,FAS, RBBP4, BAZ1A, AGPAT5, MARCH5, SEC10L1, PBK, BRIP1, KLHL24, STAT1,GTPBP3, MOBK1B, MDS032, WDR45L 393 HNRPD, WARS, SFRS2, STAT1, EIF4E, 81%79% 77% 86% 69% 66% MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, TES,DCK, CDC40, CXCL9, IRF8, CXCL10, FAS, PLK4, SLC25A11, C1QBP, NDUFA9,KPNB1, C17orf25, ME2, IFT20, RBBP4, TLK1, SLC4A4, CXCL11, RBM25, AK2,NUP210, ATP5A1, CDC42BPA, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, KLHL24,ETNK1, FLJ20641, PIK3CD 394 WARS, SFRS2, EIF4E, PRDX3, MTHFD2, 81% 90%85% 79% 85% 72% PSME2, GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, MAD2L1,CDC40, CXCL9, IRF8, CXCL10, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11,GZMB, SLC4A4, RBM25, AK2, FAS, SEC10L1, KLHL24, STAT1, KIAA0907 395WARS, SFRS2, EPAS1, PAICS, EIF4E, 85% 86% 85% 72% 69% 76% PRDX3, MTHFD2,PSME2, DLGAP4, TYMS, TES, DCK, CDC40, SLC4A4, IRF8, CXCL10, PLK4, C1QBP,NDUFA9, SLC25A11, WHSC1, CA2, ME2, FUT4, GZMB, TLK1, CXCL11, RBM25,hCAP-D3, FAS, AGPAT5, MARCH5, SEC10L1, PSAT1, HNRPD, BRIP1, STAT1, NUMB,HMGB2 396 WARS, EIF4E, MTHFD2, GMFB, DLGAP4, 81% 83% 81% 90% 73% 79%CTSS, CDC40, CXCL10, FAS, HNRPA3P1, C1QBP, NDUFA9, SLC25A11, HNRPD, ME2,FUT4, CXCL11, RBM25, ATP5A1, FLJ10534, SEC10L1, FLJ13220, PBK, BRIP1,STAT1, KPNA2, IBRDC3, RIG, NP 397 WARS, EPAS1, EIF4E, MTHFD2, PSME2, 81%83% 92% 76% 73% 76% TK1, GMFB, DLGAP4, TYMS, USP4, LMAN1, DCK, CDC40,CXCL9, IRF8, GTSE1, CXCL10, FAS, TRIM25, KITLG, SLC25A11, C1QBP, NDUFA9,KPNB1, WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, GZMB, RBM25, AK2,NUP210, ATP5A1, DDAH2, FLJ10534, MARCH5, FLJ13220, PBK, PSAT1, BRIP1,TRMT5, KLHL24, ETNK1, STAT1, SFRS7, SMURF2, SCC-112 398 WARS, SFRS2,PRDX3, PSME2, TK1, 92% 97% 88% 76% 81% 79% GMFB, DLGAP4, TYMS, TES,MAD2L1, CXCL9, GTSE1, CXCL10, PLK4, TRIM25, C1QBP, NDUFA9, KPNB1, WHSC1,C17orf25, CA2, ME2, CXCL11, GZMB, IFT20, SLC4A4, RBM25, AK2, hCAP-D3,ATP5A1, FAS, MARCH5, PBK, HNRPD, ETNK1, STAT1, HEM1, DKK1, PRDX1,ELOVL6, CD86 399 HNRPD, WARS, SFRS2, EPAS1, EIF4E, 85% 79% 88% 79% 88%76% PRDX3, MTHFD2, PSME2, MCM6, GMFB, DLGAP4, TYMS, USP4, LMAN1, CDC40,SLC4A4, CXCL9, GTSE1, CXCL10, FAS, PLK4, SLC25A11, C1QBP, NDUFA9, KPNB1,WHSC1, C17orf25, CA2, ME2, CXCL11, IFT20, RBM25, BRRN1, CDC42BPA, RBBP4,AGPAT5, MARCH5, SEC10L1, PBK, TRMT5, KLHL24, STAT1, PEG3, ASPM, NR5A2400 WARS, SFRS2, PAICS, EIF4E, SFPQ, 65% 79% 92% 86% 85% 76% PRDX3,MTHFD2, PSME2, GMFB, DLGAP4, TYMS, USP4, CTSS, LMAN1, DCK, MAD2L1,CXCL9, IRF8, CXCL10, PLK4, KITLG, C1QBP, NDUFA9, KPNB1, SLC25A11, WHSC1,C17orf25, CA2, HNRPD, ME2, CXCL11, TLK1, SLC4A4, RBM25, AK2, ATP5A1,FAS, RBBP4, BAZ1A, FLJ10534, SEC10L1, FLJ13220, PBK, PSAT1, BRIP1,KLHL24, STAT1, AMD1 401 HNRPD, WARS, EIF4E, MTHFD2, PSME2, 85% 79% 85%86% 81% 76% GBP1, TK1, GMFB, DLGAP4, TYMS, USP4, TES, MAD2L1, CXCL9,CXCL10, FAS, TRIM25, NDUFA9, WHSC1, C17orf25, CA2, ME2, CXCL11, TLK1,SLC4A4, RBM25, BRRN1, DDAH2, MARCH5, PBK, PSAT1, BRIP1, KLHL24, STAT1,LOC146909, ECT2, BM039, GTF3C4 402 WARS, EPAS1, STAT1, EIF4E, MTHFD2,81% 79% 88% 79% 81% 79% TK1, GMFB, DLGAP4, TYMS, USP4, CTSS, DCK, ARF6,CDC40, CXCL9, CXCL10, PLK4, HNRPA3P1, TRIM25, KITLG, SLC25A11, NDUFA9,WHSC1, C17orf25, CA2, HNRPD, ME2, CXCL11, IFT20, TLK1, SLC4A4, RBM25,AK2, CAMSAP1L1, ATP5A1, SOCS6, SFRS2, DDAH2, FAS, RBBP4, MARCH5,SEC10L1, FLJ13220, PBK, PSAT1, BRIP1, KLHL24, MS4A12, SMCHD1, RANBP2L1,SP110, SE57-1 403 WARS, SFRS2, EPAS1, STAT1, EIF4E, 73% 86% 81% 83% 69%79% MTHFD2, PSME2, MCM6, TK1, GMFB, DLGAP4, TYMS, TES, CDC40, SLC4A4,CXCL9, IRF8, GTSE1, CXCL10, FAS, CHEK1, SLC25A1, C1QBP, NDUFA9, WHSC1,C17orf25, CA2, ME2, FUT4, TLK1, RBM25, CAMSAP1L1, hCAP-D3, DDAH2, RBBP4,FLJ10534, PBK, PSAT1, BRIP1, KLHL24, ETNK1, CAND1

Example 20 Specific Application of Prediction Methods

In selection of the gene signatures described here, two differentstatistical methods were used to characterise the signatures: k-nearestneighbours, and support vector machines. These methods are provided aspackages to the R statistical software system (ref), through thepackages class (ref) and e1071 (ref).

The signatures described in this document were tested as follows. Inboth cases, the data used to develop the prediction models for a givensignature were the gene expression values (raw normalised intensitiesfrom the Affymetrix array data) for the probes corresponding to genesthat comprise that signature, across both recurrent and non-recurrentsamples:

-   -   For k-nearest neighbours, we used leave-one-out cross validation        with k=1 and k=3 to obtain sensitivity (proportion of positive,        i.e. recurrent, samples correctly classified) and specificity        (proportion of negative samples, i.e. non-recurrent samples        correctly classified) described in table 9    -   The dataset was used to generate leave-one-out cross-validation        sensitivity and specificity data using the following        support-vector machine parameters: The support vector machine        models were generated using a linear kernel, and all other        parameters used were the default values obtained from the svm        function of the e1071 package.

Note the genes comprising the signatures were themselves obtained fromthe list of significantly differentially expressed probes, and thosefrom the list of genes which were found to correlate with genes from theNZ 22-gene signature. In some cases there was more than one significant(or correlated) probe per gene. In these cases, the prediction modelsused the median intensity data across all significant probes (i.e. thosein the significant probe list, see table 1) for that gene.

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Wherein in the description reference has been made to integers orcomponents having known equivalents, such equivalents are hereinincorporated as if individually set fourth.

Although the invention has been described by way of example and withreference to possible embodiments thereof, it is to be appreciated thatimprovements and/or modifications may be made without departing from thescope thereof.

What is claimed is:
 1. A prognostic signature for determiningprogression of CRC, comprising two or more genes selected from Tables 1and
 2. 2. The signature of claim 1, selected from any one of thesignatures in any one of Tables 3, 4 or Table
 9. 3. A device fordetermining prognosis of CRC, comprising: a substrate having one or morelocations thereon, each location having two or more oligonucleotidesthereon, each oligonucleotide selected from the group of genes fromTables 1 and
 2. 4. The device of claim 3, wherein said the two or moreoligonucleotides are a prognostic signature selected from in any one ofTables 3, 4 or Table
 9. 5. A method for determining the prognosis of CRCin a patient, comprising the steps of; (i) determining the expressionlevel of a prognostic signature comprising two or more genes from Tables1 and 2 in CRC tumour sample from the patient, (ii) applying apredictive model, established by applying a predictive method toexpressions levels of the predictive signature in recurrent andnon-recurrent tumour samples, (iii) establishing a prognosis.
 6. Themethod of claim 5, wherein the signature is selected from any one ofTables 3, 4 or Table
 9. 7. The method of claim 5, wherein saidpredictive method is selected from the group consisting of linearmodels, support vector machines, neural networks, classification andregression trees, ensemble learning methods, discriminant analysis,nearest neighbor method, bayesian networks, independent componentsanalysis.
 8. The method of any one of claims 5 to 7, wherein the step ofdetermining the expression level of a prognostic signature is carriedout by detecting the expression level of mRNA of each gene.
 9. Themethod of any one of claims 5 to 7, wherein the step of determining theexpression level of a prognostic signature is carried out by detectingthe expression level of cDNA of each gene.
 10. The method of claim 9,wherein the step of determining the expression level of a prognosticsignature is carried out using a nucleotide complementary to at least aportion of said cDNA.
 11. The method of claim 8, wherein the step ofdetermining the expression level of a prognostic signature is carriedout using qPCR method using a forward primer and a reverse primer. 12.The method of claim 8, wherein the step of determining the expressionlevel of a prognostic signature is carried out using a device accordingto claim 3 or claim
 4. 13. The method of any one of claims 5 to 7,wherein the step of determining the expression level of a prognosticsignature is carried out by detecting the expression level of theprotein of each marker.
 14. The method of any one of claims 5 to 7,wherein the step of determining the expression level of a prognosticsignature is carried out by detecting the expression level of thepeptide of each marker.
 15. The method of claim 12 or claim 13, whereinsaid step of detecting is carried out using an antibody directed againsteach marker.
 16. The method of any one of claims 12 to 14, wherein saidstep of detecting is carried out using a sandwich-type immunoassaymethod.
 17. The method of any one of claims 12 to 15, wherein saidantibody is a monoclonal antibody.
 18. The method of any one of claims12 to 15, wherein said antibody is a polyclonal antiserum.